This project makes use of "biomimetic behavioral engineering" in which adaptive strategies used by animals in the real world are applied to the development of autonomous robots. The key elements of the biomimetic approach are to observe and understand a survival behavior exhibited in nature, to create a mathematical model and simulation capability for that behavior, to modify and optimize the behavior for a desired robotics application, and to implement it. The application described in this report is dynamic soaring, a behavior that certain sea birds use to extract flight energy from laminar wind velocity gradients in the shallow atmospheric boundary layer directly above the ocean surface. Theoretical calculations, computational proof-of-principle demonstrations, and the first instrumented experimental flight test data for dynamic soaring are presented to address the feasibility of developing dynamic soaring flight control algorithms to sustain the flight of unmanned airborne vehicles (UAVs). Both hardware and software were developed for this application. Eight-foot custom foam sailplanes were built and flown in a steep shear gradient. A logging device was designed and constructed with custom software to record flight data during dynamic soaring maneuvers. A computational toolkit was developed to simulate dynamic soaring in special cases and with a full 6-degree of freedom flight dynamics model in a generalized time-dependent wind field. Several 3-dimensional visualization tools were built to replay the flight simulations. A realistic aerodynamics model of an eight-foot sailplane was developed using measured aerodynamic derivatives. Genetic programming methods were developed and linked to the simulations and visualization tools. These tools can now be generalized for other biomimetic behavior applications. This work was carried out in 2000 and 2001, and until now its results have only been available in an internal Sandia report.
Concurrent sound associated with very bright meteors manifests as popping, hissing, and faint rustling sounds occurring simultaneously with the arrival of light from meteors. Numerous instances have been documented with â '11 to â '13 brightness. These sounds cannot be attributed to direct acoustic propagation from the upper atmosphere for which travel time would be several minutes. Concurrent sounds must be associated with some form of electromagnetic energy generated by the meteor, propagated to the vicinity of the observer, and transduced into acoustic waves. Previously, energy propagated from meteors was assumed to be RF emissions. This has not been well validated experimentally. Herein we describe experimental results and numerical models in support of photoacoustic coupling as the mechanism. Recent photometric measurements of fireballs reveal strong millisecond flares and significant brightness oscillations at frequencies ≥40 Hz. Strongly modulated light at these frequencies with sufficient intensity can create concurrent sounds through radiative heating of common dielectric materials like hair, clothing, and leaves. This heating produces small pressure oscillations in the air contacting the absorbers. Calculations show that â '12 brightness meteors can generate audible sound at ∼25 dB SPL. The photoacoustic hypothesis provides an alternative explanation for this longstanding mystery about generation of concurrent sounds by fireballs.
The 2015 Planetary Defense Conference (2015 PDC) was held in Frascati, Italy on April 13-17 by the International Academy of Astronautics (IAA). In addition to customary technical sessions, we performed the first week-long threat exercise designed to simulate and examine the process of decision making that would accompany the discovery and response to an asteroid on a collision course with Earth. Our role in the exercise was to develop and present a plausible scenario that would be of interest to as many participants as possible while considering the broad diversity in technical expertise, approach, values, missions, and national affiliations of the conference attendees. Moreover, we strove to present a reasonable sequence of events spanning several years that would provide many opportunities for collective decision making under uncertainty by parties likely to have conflicting interests. In order to hold the attention of the participants throughout the week we tried to create a scenario that would be as dramatic as possible - including cliffhangers and unexpected turns of events - but without sacrificing realism. This allowed us to discuss a wide range of potential responses, including kinetic and nuclear deflection, and potential outcomes, including tsunami-forming ocean impacts, crater-forming land impacts, and airbursts by objects over a large size range. In addition to creating the scenario, members of our team served on an expert panel in a role-playing exercise that included participants acting as world leaders of nations, both directly and indirectly affected members of the public in at-risk areas, and the media. This paper summarizes the exercise, focusing on physical and infrastructure modeling. The exercise spanned the entire week, with daily injects (or updates) of new observed data about what was currently known on the imaginary date. We presented models of potential physical effects and resulting infrastructure damage, with emphasis on the uncertainties. Seven updates spanned most of the time between when the asteroid (dubbed 2015 PDC) was discovered on April 13, 2015, and its impact date of September 3, 2022. Information about the orbit and technical response options were presented as a set of faux press releases that were made available to participants prior to each briefing. The scenario was based on an actual calculated orbit to provide as much realism as possible. The physical effects at each stage were predicted by using simulations for airburst and tsunami generation, and a shallow water model for tsunami propagation. Maps were generated using tools developed for the National Infrastructure Simulation and Analysis Center (NISAC), and were presented by expert panelists as part of a mock press briefing at each inject. We present the contents of those press briefings and put them into context with the threat exercise.
I have performed a series of high-resolution hydrocode simulations to generate “source functions” for tsunami simulations as part of a proof-of-principle effort to determine whether or not the downward momentum from an asteroid airburst can couple energy into a dangerous tsunami in deep water. My new CTH simulations show enhanced momentum multiplication relative to a nuclear explosion of the same yield. Extensive sensitivity and convergence analyses demonstrate that results are robust and repeatable for simulations with sufficiently high resolution using adaptive mesh refinement. I have provided surface overpressure and wind velocity fields to tsunami modelers to use as time-dependent boundary conditions and to test the hypothesis that this mechanism can enhance the strength of the resulting shallow-water wave. The enhanced momentum result suggests that coupling from an over-water plume-forming airburst could be a more efficient tsunami source mechanism than a collapsing impact cavity or direct air blast alone, but not necessarily due to the originally-proposed mechanism. This result has significant implications for asteroid impact risk assessment and airburst-generated tsunami will be the focus of a NASA-sponsored workshop at the Ames Research Center next summer, with follow-on funding expected.
We present a new analysis of airburst risk based on updated estimates for the population of undiscovered NEOs, taking into account the enhanced damage potential of directed airbursts. We define airbursts as events in which small (meters to tens-of-meters in diameter) asteroids deposit most of their energy in the atmosphere as large bolides and where the total energy is comparable to or greater than small nuclear explosions (>0.1 kilotons of TNT). Our tens-of-meter population estimate from optical surveys is now much closer to bolide frequency estimates, resolving most of an earlier discrepancy. Our Tunguska-class (∼40 meters) population estimate has doubled, and Chelyabinsk-class (∼20 meters) has increased by a factor of 2.6. Uncertainty in this population remains quite large, and can only be unambiguously reduced by expanded surveys focused on objects in the tens-of-meters size range. The assessed risk from this population is also increasing for two reasons. First, airbursts are significantly more damaging than assumed in the original risk assessments, because for typical impact geometries they more efficiently couple energy to the surface than nuclear explosions of the same energy. Second, the greater numbers mean that they are more frequent than previously thought. We review the evidence that asteroid airbursts are more damaging than nuclear explosions, and provide arguments that such events are more frequent.
High-speed photometric observations of meteor fireballs have shown that they often produce high-amplitude light oscillations with frequency components in the kHz range, and in some cases exhibit strong millisecond flares. We built a light source with similar characteristics and illuminated various materials in the laboratory, generating audible sounds. Models suggest that light oscillations and pulses can radiatively heat dielectric materials, which in turn conductively heats the surrounding air on millisecond timescales. The sound waves can be heard if the illuminated material is sufficiently close to the observer’s ears. The mechanism described herein may explain many reports of meteors that appear to be audible while they are concurrently visible in the sky and too far away for sound to have propagated to the observer. This photoacoustic (PA) explanation provides an alternative to electrophonic (EP) sounds hypothesized to arise from electromagnetic coupling of plasma oscillation in the meteor wake to natural antennas in the vicinity of an observer.
This study began with a challenge from program area managers at Sandia National Laboratories to technical staff in the energy, climate, and infrastructure security areas: apply a systems-level perspective to existing science and technology program areas in order to determine technology gaps, identify new technical capabilities at Sandia that could be applied to these areas, and identify opportunities for innovation. The Arctic was selected as one of these areas for systems level analyses, and this report documents the results. In this study, an emphasis was placed on the arctic atmosphere since Sandia has been active in atmospheric research in the Arctic since 1997. This study begins with a discussion of the challenges and benefits of analyzing the Arctic as a system. It goes on to discuss current and future needs of the defense, scientific, energy, and intelligence communities for more comprehensive data products related to the Arctic; assess the current state of atmospheric measurement resources available for the Arctic; and explain how the capabilities at Sandia National Laboratories can be used to address the identified technological, data, and modeling needs of the defense, scientific, energy, and intelligence communities for Arctic support.
We describe the computational simulations and damage assessments that we provided in support of a tabletop exercise (TTX) at the request of NASA's Near-Earth Objects Program Office. The overall purpose of the exercise was to assess leadership reactions, information requirements, and emergency management responses to a hypothetical asteroid impact with Earth. The scripted exercise consisted of discovery, tracking, and characterization of a hypothetical asteroid; inclusive of mission planning, mitigation, response, impact to population, infrastructure and GDP, and explicit quantification of uncertainty. Participants at the meeting included representatives of NASA, Department of Defense, Department of State, Department of Homeland Security/Federal Emergency Management Agency (FEMA), and the White House. The exercise took place at FEMA headquarters. Sandia's role was to assist the Jet Propulsion Laboratory (JPL) in developing the impact scenario, to predict the physical effects of the impact, and to forecast the infrastructure and economic losses. We ran simulations using Sandia's CTH hydrocode to estimate physical effects on the ground, and to produce contour maps indicating damage assessments that could be used as input for the infrastructure and economic models. We used the FASTMap tool to provide estimates of infrastructure damage over the affected area, and the REAcct tool to estimate the potential economic severity expressed as changes to GDP (by nation, region, or sector) due to damage and short-term business interruptions.
Climate change, through drought, flooding, storms, heat waves, and melting Arctic ice, affects the production and flow of resource within and among geographical regions. The interactions among governments, populations, and sectors of the economy require integrated assessment based on risk, through uncertainty quantification (UQ). This project evaluated the capabilities with Sandia National Laboratories to perform such integrated analyses, as they relate to (inter)national security. The combining of the UQ results from climate models with hydrological and economic/infrastructure impact modeling appears to offer the best capability for national security risk assessments.
In safety engineering, performance metrics are defined using probabilistic risk assessments focused on the low-probability, high-consequence tail of the distribution of possible events, as opposed to best estimates based on central tendencies. We frame the climate change problem and its associated risks in a similar manner. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We therefore propose the use of specialized statistical surrogate models (SSMs) for the purpose of exploring the probability law of various climate variables of interest. A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field. The SSM can be calibrated to available spatial and temporal data from existing climate databases, e.g., the Program for Climate Model Diagnosis and Intercomparison (PCMDI), or to a collection of outputs from a General Circulation Model (GCM), e.g., the Community Earth System Model (CESM) and its predecessors. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework is developed to provide quantitative measures of confidence, via Bayesian credible intervals, in the use of the proposed approach to assess these risks.
The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) made extensive use of coordinated simulations by 18 international modeling groups using a variety of coupled general circulation models (GCMs) with different numerics, algorithms, resolutions, physics models, and parameterizations. These simulations span the 20th century and provide forecasts for various carbon emissions scenarios in the 21st century. All the output from this panoply of models is made available to researchers on an archive maintained by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) at LLNL. I have downloaded this data and completed the first steps toward a statistical analysis of these ensembles for the US Southwest. This constitutes the final report for a late start LDRD project. Complete analysis will be the subject of a forthcoming report.
Because the potential effects of climate change are more severe than had previously been thought, increasing focus on uncertainty quantification is required for risk assessment needed by policy makers. Current scientific efforts focus almost exclusively on establishing best estimates of future climate change. However, the greatest consequences occur in the extreme tail of the probability density functions for climate sensitivity (the 'high-sensitivity tail'). To this end, we are exploring the impacts of newly postulated, highly uncertain, but high-consequence physical mechanisms to better establish the climate change risk. We define consequence in terms of dramatic change in physical conditions and in the resulting socioeconomic impact (hence, risk) on populations. Although we are developing generally applicable risk assessment methods, we have focused our initial efforts on uncertainty and risk analyses for the Arctic region. Instead of focusing on best estimates, requiring many years of model parameterization development and evaluation, we are focusing on robust emergent phenomena (those that are not necessarily intuitive and are insensitive to assumptions, subgrid-parameterizations, and tunings). For many physical systems, under-resolved models fail to generate such phenomena, which only develop when model resolution is sufficiently high. Our ultimate goal is to discover the patterns of emergent climate precursors (those that cannot be predicted with lower-resolution models) that can be used as a 'sensitivity fingerprint' and make recommendations for a climate early warning system that would use satellites and sensor arrays to look for the various predicted high-sensitivity signatures. Our initial simulations are focused on the Arctic region, where underpredicted phenomena such as rapid loss of sea ice are already emerging, and because of major geopolitical implications associated with increasing Arctic accessibility to natural resources, shipping routes, and strategic locations. We anticipate that regional climate will be strongly influenced by feedbacks associated with a seasonally ice-free Arctic, but with unknown emergent phenomena.
Ongoing simulations of low-altitude airbursts from hypervelocity asteroid impacts have led to a re-evaluation of the impact hazard that accounts for the enhanced damage potential relative to the standard point-source approximations. Computational models demonstrate that the altitude of maximum energy deposition is not a good estimate of the equivalent height of a point explosion, because the center of mass of an exploding projectile maintains a significant fraction of its initial momentum and is transported downward in the form of a high-temperature jet of expanding gas. This 'fireball' descends to a depth well beneath the burst altitude before its velocity becomes subsonic. The time scale of this descent is similar to the time scale of the explosion itself, so the jet simultaneously couples both its translational and its radial kinetic energy to the atmosphere. Because of this downward flow, larger blast waves and stronger thermal radiation pulses are experienced at the surface than would be predicted for a nuclear explosion of the same yield at the same burst height. For impacts with a kinetic energy below some threshold value, the hot jet of vaporized projectile loses its momentum before it can make contact with the Earth's surface. The 1908 Tunguska explosion is the largest observed example of this first type of airburst. For impacts above the threshold, the fireball descends all the way to the ground, where it expands radially, driving supersonic winds and radiating thermal energy at temperatures that can melt silicate surface materials. The Libyan Desert Glass event, 29 million years ago, may be an example of this second, larger, and more destructive type of airburst. The kinetic energy threshold that demarcates these two airburst types depends on asteroid velocity, density, strength, and impact angle. Airburst models, combined with a reexamination of the surface conditions at Tunguska in 1908, have revealed that several assumptions from the earlier analyses led to erroneous conclusions, resulting in an overestimate of the size of the Tunguska event. Because there is no evidence that the Tunguska fireball descended to the surface, the yield must have been about 5 megatons or lower. Better understanding of airbursts, combined with the diminishing number of undiscovered large asteroids, leads to the conclusion that airbursts represent a large and growing fraction of the total impact threat.
Keigwin (Science 274:1504-1508, 1996) reconstructed the sea surface temperature (SST) record in the northern Sargasso Sea to document natural climate variability in recent millennia. The annual average SST proxy used {delta}{sup 18}O in planktonic foraminifera in a radiocarbon-dated 1990 Bermuda Rise box core. Keigwin's Fig. 4B (K4B) shows a 50-year-averaged time series along with four decades of SST measurements from Station S near Bermuda, demonstrating that the Sargasso Sea is now at its warmest in more than 400 years, and well above the most recent box-core temperature. Taken together, Station S and paleo-temperatures suggest there was an acceleration of warming in the 20th century, though this was not an explicit conclusion of the paper. Keigwin concluded that anthropogenic warming may be superposed on a natural warming trend. In an unpublished paper circulated with the anti-Kyoto 'Oregon Petition,' Robinson et al. ('Environmental Effects of Increased Atmospheric Carbon Dioxide,' 1998) reproduced K4B but (1) omitted Station S data, (2) incorrectly stated that the time series ended in 1975, (3) conflated Sargasso Sea data with global temperature, and (4) falsely claimed that Keigwin showed global temperatures 'are still a little below the average for the past 3,000 years.' Keigwin's Fig. 2 showed that {delta}{sup 18}O has increased over the past 6000 years, so SSTs calculated from those data would have a long term decrease. Thus, it is inappropriate to compare present-day SST to a long term mean unless the trend is removed. Slight variations of Robinson et al. (1998) have been repeatedly published with different author rotations. Various mislabeled, improperly-drawn, and distorted versions of K4B have appeared in the Wall Street Journal, in weblogs, and even as an editorial cartoon-all supporting baseless claims that current temperatures are lower than the long-term mean, and traceable to Robinson's misrepresentation with Station S data removed. In 2007, Robinson added a fictitious 2006 temperature that is significantly lower than the measured data. This doctored version of K4B with fabricated data was reprinted in a 2008 Heartland Institute advocacy report, 'Nature, Not Human Activity, Rules the Climate.'
The YDB impact hypothesis of Firestone et al. (2007) is so extremely improbable it can be considered statistically impossible in addition to being physically impossible. Comets make up only about 1% of the population of Earth-crossing objects. Broken comets are a vanishingly small fraction, and only exist as Earth-sized clusters for a very short period of time. Only a small fraction of impacts occur at angles as shallow as proposed by the YDB impact authors. Events that are exceptionally unlikely to take place in the age of the Universe are 'statistically impossible'. The size distribution of Earth-crossing asteroids is well-constrained by astronomical observations, DoD satellite bolide frequencies, and the cratering record. This distribution can be transformed to a probability density function (PDF) for the largest expected impact of the past 20,000 years. The largest impact of any kind expected over the period of interest is 250 m. Anything larger than 2 km is exceptionally unlikely (probability less than 1%). The impact hypothesis does not rely on any sound physical model. A 4-km diameter comet, even if it fragmented upon entry, would not disperse or explode in the atmosphere. It would generate a crater about 50 km in diameter with a transient cavity as deep as 10 km. There is no evidence for such a large, young crater associated with the YDB. There is no model to suggest that a comet impact of this size is capable of generating continental-wide fires or blast damage, and there is no physical mechanism that could cause a 4-km comet to explode at the optimum height of 500 km. The highest possible altitude for a cometary optimum height is about 15 km, for a 120-m diameter comet. To maximize blast and thermal damage, a 4-km comet would have to break into tens of thousands fragments of this size and spread out over the entire continent, but that would require lateral forces that greatly exceed the drag force, and would not conserve energy. Airbursts are decompression explosions in which projectile material reaches high temperature but not high pressure states. Meteoritic diamonds would be vaporized. Nanodiamonds at the YDB are not evidence for an airburst or for an impact.
Global monitoring systems that have high spatial and temporal resolution, with long observational baselines, are needed to provide situational awareness of the Earth's climate system. Continuous monitoring is required for early warning of high-consequence climate change and to help anticipate and minimize the threat. Global climate has changed abruptly in the past and will almost certainly do so again, even in the absence of anthropogenic interference. It is possible that the Earth's climate could change dramatically and suddenly within a few years. An unexpected loss of climate stability would be equivalent to the failure of an engineered system on a grand scale, and would affect billions of people by causing agricultural, economic, and environmental collapses that would cascade throughout the world. The probability of such an abrupt change happening in the near future may be small, but it is nonzero. Because the consequences would be catastrophic, we argue that the problem should be treated with science-informed engineering conservatism, which focuses on various ways a system can fail and emphasizes inspection and early detection. Such an approach will require high-fidelity continuous global monitoring, informed by scientific modeling.
The Arctic region is rapidly changing in a way that will affect the rest of the world. Parts of Alaska, western Canada, and Siberia are currently warming at twice the global rate. This warming trend is accelerating permafrost deterioration, coastal erosion, snow and ice loss, and other changes that are a direct consequence of climate change. Climatologists have long understood that changes in the Arctic would be faster and more intense than elsewhere on the planet, but the degree and speed of the changes were underestimated compared to recent observations. Policy makers have not yet had time to examine the latest evidence or appreciate the nature of the consequences. Thus, the abruptness and severity of an unfolding Arctic climate crisis has not been incorporated into long-range planning. The purpose of this report is to briefly review the physical basis for global climate change and Arctic amplification, summarize the ongoing observations, discuss the potential consequences, explain the need for an objective risk assessment, develop scenarios for future change, review existing modeling capabilities and the need for better regional models, and finally to make recommendations for Sandia's future role in preparing our leaders to deal with impacts of Arctic climate change on national security. Accurate and credible regional-scale climate models are still several years in the future, and those models are essential for estimating climate impacts around the globe. This study demonstrates how a scenario-based method may be used to give insights into climate impacts on a regional scale and possible mitigation. Because of our experience in the Arctic and widespread recognition of the Arctic's importance in the Earth climate system we chose the Arctic as a test case for an assessment of climate impacts on national security. Sandia can make a swift and significant contribution by applying modeling and simulation tools with internal collaborations as well as with outside organizations. Because changes in the Arctic environment are happening so rapidly, a successful program will be one that can adapt very quickly to new information as it becomes available, and can provide decision makers with projections on the 1-5 year time scale over which the most disruptive, high-consequence changes are likely to occur. The greatest short-term impact would be to initiate exploratory simulations to discover new emergent and robust phenomena associated with one or more of the following changing systems: Arctic hydrological cycle, sea ice extent, ocean and atmospheric circulation, permafrost deterioration, carbon mobilization, Greenland ice sheet stability, and coastal erosion. Sandia can also contribute to new technology solutions for improved observations in the Arctic, which is currently a data-sparse region. Sensitivity analyses have the potential to identify thresholds which would enable the collaborative development of 'early warning' sensor systems to seek predicted phenomena that might be precursory to major, high-consequence changes. Much of this work will require improved regional climate models and advanced computing capabilities. Socio-economic modeling tools can help define human and national security consequences. Formal uncertainty quantification must be an integral part of any results that emerge from this work.
The purpose of this nine-week project was to advance the understanding of low-altitude airbursts by developing the means to model them at extremely high resolution in order to span the scales of entry physics as well as blast wave and plume formation. Small asteroid impacts on Earth are a recognized hazard, but the full nature of the threat is still not well understood. We used shock physics codes to discover emergent phenomena associated with low-altitude airbursts such as the Siberian Tunguska event of 1908 and the Egyptian glass-forming event 29 million years ago. The planetary defense community is beginning to recognize the significant threat from such airbursts. Low-altitude airbursts are the only class of impacts that have a significant probability of occurring within a planning time horizon. There is roughly a 10% chance of a megaton-scale low-altitude airburst event in the next decade.The first part of this LDRD final project report is a preprint of our proceedings paper associated with the plenary presentation at the Hypervelocity Impact Society 2007 Symposium in Williamsburg, Virginia (International Journal of Impact Engineering, in press). The paper summarizes discoveries associated with a series of 2D axially-symmetric CTH simulations. The second part of the report contains slides from an invited presentation at the American Geophysical Union Fall 2007 meeting in San Francisco. The presentation summarizes the results of a series of 3D oblique impact simulations of the 1908 Tunguska explosion. Because of the brevity of this late-start project, the 3D results have not yet been written up for a peer-reviewed publication. We anticipate the opportunity to eventually run simulations that include the actual topography at Tunguska, at which time these results will be published.3
We present the initial stages of development of new agent-based computational methods to generate and test hypotheses about linkages between environmental change and international instability. This report summarizes the first year's effort of an originally proposed three-year Laboratory Directed Research and Development (LDRD) project. The preliminary work focused on a set of simple agent-based models and benefited from lessons learned in previous related projects and case studies of human response to climate change and environmental scarcity. Our approach was to define a qualitative model using extremely simple cellular agent models akin to Lovelock's Daisyworld and Schelling's segregation model. Such models do not require significant computing resources, and users can modify behavior rules to gain insights. One of the difficulties in agent-based modeling is finding the right balance between model simplicity and real-world representation. Our approach was to keep agent behaviors as simple as possible during the development stage (described herein) and to ground them with a realistic geospatial Earth system model in subsequent years. This work is directed toward incorporating projected climate data--including various C02 scenarios from the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report--and ultimately toward coupling a useful agent-based model to a general circulation model.3
We summarize the results of a project to develop evolutionary computing methods for the design of behaviors of embodied agents in the form of autonomous vehicles. We conceived and implemented a strategy called graduated embodiment. This method allows high-level behavior algorithms to be developed using genetic programming methods in a low-fidelity, disembodied modeling environment for migration to high-fidelity, complex embodied applications. This project applies our methods to the problem domain of robot navigation using adaptive waypoints, which allow navigation behaviors to be ported among autonomous mobile robots with different degrees of embodiment, using incremental adaptation and staged optimization. Our approach to biomimetic behavior engineering is a hybrid of human design and artificial evolution, with the application of evolutionary computing in stages to preserve building blocks and limit search space. The methods and tools developed for this project are directly applicable to other agent-based modeling needs, including climate-related conflict analysis, multiplayer training methods, and market-based hypothesis evaluation.
This white paper represents a summary of work intended to lay the foundation for development of a climatological/agent model of climate-induced conflict. The paper combines several loosely-coupled efforts and is the final report for a four-month late-start Laboratory Directed Research and Development (LDRD) project funded by the Advanced Concepts Group (ACG). The project involved contributions by many participants having diverse areas of expertise, with the common goal of learning how to tie together the physical and human causes and consequences of climate change. We performed a review of relevant literature on conflict arising from environmental scarcity. Rather than simply reviewing the previous work, we actively collected data from the referenced sources, reproduced some of the work, and explored alternative models. We used the unfolding crisis in Darfur (western Sudan) as a case study of conflict related to or triggered by climate change, and as an exercise for developing a preliminary concept map. We also outlined a plan for implementing agents in a climate model and defined a logical progression toward the ultimate goal of running both types of models simultaneously in a two-way feedback mode, where the behavior of agents influences the climate and climate change affects the agents. Finally, we offer some ''lessons learned'' in attempting to keep a diverse and geographically dispersed group working together by using Web-based collaborative tools.
This project makes use of ''biomimetic behavioral engineering'' in which adaptive strategies used by animals in the real world are applied to the development of autonomous robots. The key elements of the biomimetic approach are to observe and understand a survival behavior exhibited in nature, to create a mathematical model and simulation capability for that behavior, to modify and optimize the behavior for a desired robotics application, and to implement it. The application described in this report is dynamic soaring, a behavior that certain sea birds use to extract flight energy from laminar wind velocity gradients in the shallow atmospheric boundary layer directly above the ocean surface. Theoretical calculations, computational proof-of-principle demonstrations, and the first instrumented experimental flight test data for dynamic soaring are presented to address the feasibility of developing dynamic soaring flight control algorithms to sustain the flight of unmanned airborne vehicles (UAVs). Both hardware and software were developed for this application. Eight-foot custom foam sailplanes were built and flown in a steep shear gradient. A logging device was designed and constructed with custom software to record flight data during dynamic soaring maneuvers. A computational toolkit was developed to simulate dynamic soaring in special cases and with a full 6-degree of freedom flight dynamics model in a generalized time-dependent wind field. Several 3-dimensional visualization tools were built to replay the flight simulations. A realistic aerodynamics model of an eight-foot sailplane was developed using measured aerodynamic derivatives. Genetic programming methods were developed and linked to the simulations and visualization tools. These tools can now be generalized for other biomimetic behavior applications.
GENESIS Version 2.0 is a general circulation model developed at the National Center for Atmospheric Research (NCAR) and is the principal code that is used by paleoclimatologists to model climate at various times throughout Earth's history. The primary result of this LDRD project has been the development of a distributed-memory parallel version of GENESIS, leading to a significant performance enhancement on commodity-based, large-scale computing platforms like the CPlant. The shared-memory directives of the original version were replaced by MPI calls in the new version of GENESIS. This was accomplished by means of parallel decomposition over latitude strip domains. The code achieved a parallel speedup of four times that of the shared-memory parallel version at R15 resolution. T106 resolution runs 20 times faster than the NCAR serial version on 20 nodes of the CPlant. As part of the project, GENESIS was used to model the climatic effects of an orbiting debris ring due to a large planetary impact event.