Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “interacting agent systems”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

A Survey of Formal Methods for Intelligent Swarms

Swarms of intelligent autonomous spacecraft, involving complex behaviors and interactions, are being proposed for future space exploration missions. Such missions provide greater flexibility and offer the possibility of gathering more science data than traditional single spacecraft missions. The emergent properties of swarms make these missions powerful, but simultaneously far more difficult to design, and to assure that the proper behaviors will emerge. These missions are also considerably more complex than previous types of missions, and NASA, like other organizations, has little experience in developing or in verifying and validating these types of missions. A significant challenge when verifying and validating swarms of intelligent interacting agents is how to determine that the possible exponential interactions and emergent behaviors are producing the desired results. Assuring correct behavior and interactions of swarms will be critical to mission success. The Autonomous Nano Technology Swarm (ANTS) mission is an example of one of the swarm types of missions NASA is considering. The ANTS mission will use a swarm of picospacecraft that will fly from Earth orbit to the Asteroid Belt. Using an insect colony analogy, ANTS will be composed of specialized workers for asteroid exploration. Exploration would consist of cataloguing the mass, density, morphology, and chemical composition of the asteroids, including any anomalous concentrations of specific minerals. To perform this task, ANTS would carry miniaturized instruments, such as imagers, spectrometers, and detectors. Since ANTS and other similar missions are going to consist of autonomous spacecraft that may be out of contact with the earth for extended periods of time, and have low bandwidths due to weight constraints, it will be difficult to observe improper behavior and to correct any errors after launch. Providing V&V (verification and validation) for this type of mission is new to NASA, and represents the cutting edge in system correctness, and requires higher levels of assurance than other (traditional) missions that use a single or small number of spacecraft that are deterministic in nature and have near continuous communication access. One of the highest possible levels of assurance comes from the application of formal methods. Formal methods are mathematics-based tools and techniques for specifying and verifying (software and hardware) systems. They are particularly useful for specifying complex parallel systems, such as exemplified by the ANTS mission, where the entire system is difficult for a single person to fully understand, a problem that is multiplied with multiple developers. Once written, a formal specification can be used to prove properties of a system (e.g., the underlying system will go from one state to another or not into a specific state) and check for particular types of errors (e.g., race or livelock conditions). A formal specification can also be used as input to a model checker for further validation. This report gives the results of a survey of formal methods techniques for verification and validation of space missions that use swarm technology. Multiple formal methods were evaluated to determine their effectiveness in modeling and assuring the behavior of swarms of spacecraft using the ANTS mission as an example system. This report is the first result of the project to determine formal approaches that are promising for formally specifying swarm-based systems. From this survey, the most promising approaches were selected and are discussed relative to their possible application to the ANTS mission. Future work will include the application of an integrated approach, based on the selected approaches identified in this report, to the formal specification of the ANTS mission.

Truszkowski, Walt↗
DOE OSTI2020

Optimal carbon storage reservoir management through deep reinforcement learning

Model-based optimization plays a central role in energy system design and management. The complexity and high-dimensionality of many process-level models, especially those used for geosystem energy exploration and utilization, often lead to formidable computational costs when the dimension of decision space is also large. This work adopts elements of recently advanced deep learning techniques to solve a sequential decision-making problem in applied geosystem management. Specifically, a deep reinforcement learning framework was formed for optimal multiperiod planning, in which a deep Q-learning network (DQN) agent was trained to maximize rewards by learning from high-dimensional inputs and from exploitation of its past experiences. To expedite computation, deep multitask learning was used to approximate high-dimensional, multistate transition functions. Both DQN and deep multitask learning are pattern based. As a demonstration, the framework was applied to optimal carbon sequestration reservoir planning using two different types of management strategies: monitoring only and brine extraction. Both strategies are designed to mitigate potential risks due to pressure buildup. Results show that the DQN agent can identify the optimal policies to maximize the reward for given risk and cost constraints. Finally, experiments also show that knowledge the agent gained from interacting with one environment is largely preserved when deploying the same agent in other similar environments.

15 GEOTHERMAL ENERGY↗
NASA NTRS2014

Proto-Examples of Data Access and Visualization Components of a Potential Cloud-Based GEOSS-AI System

Once a research or application problem has been identified, one logical next step is to search for available relevant data products. Thus, an early component of a potential GEOSS-AI system, in the continuum between observations and end point research, applications, and decision making, would be one that enables transparent data discovery and access by users. Such a component might be effected via the systems data agents. Presumably, some kind of data cataloging has already been implemented, e.g., in the GEOSS Common Infrastructure (GCI). Both the agents and cataloging could also leverage existing resources external to the system. The system would have some means to accept and integrate user-contributed agents. The need or desirability for some data format internal to the system should be evaluated. Another early component would be one that facilitates browsing visualization of the data, as well as some basic analyses.Three ongoing projects at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provide possible proto-examples of potential data access and visualization components of a cloud-based GEOSS-AI system. 1. Reorganizing data archived as time-step arrays to point-time series (data rods), as well as leveraging the NASA Simple Subset Wizard (SSW), to significantly increase the number of data products available, at multiple NASA data centers, for production as on-the-fly (virtual) data rods. SSWs data discovery is based on OpenSearch. Both pre-generated and virtual data rods are accessible via Web services. 2. Developing Web Feature Services to publish the metadata, and expose the locations, of pre-generated and virtual data rods in the GEOSS Portal and enable direct access of the data via Web services. SSW is also leveraged to increase the availability of both NASA and non-NASA data.3.Federating NASA Giovanni (Geospatial Interactive Online Visualization and Analysis Interface), for multi-sensor data exploration, that would allow each cooperating data center, currently the NASA Distributed Active Archive Centers (DAACs), to configure its own Giovanni deployment, while also allowing all the deployments to incorporate each others data. A federated Giovanni comprises Giovanni Virtual Machines, which can be run on local servers or in the cloud.

access↗
DOE OSTI2025

Organophosphorus Binding Thermodynamics in Metal–Organic Frameworks: Interplay between Oxidation State, Lewis Acidity, and Node Structure

Organophosphorus compounds, including nerve agents and pesticides, represent a class of toxic chemicals causing harm to troops, civilians, and the environment. Metal–organic frameworks (MOFs) have emerged as a class of highly porous, crystalline, tunable materials adept at both capturing and catalytically neutralizing these harmful toxins. In particular, MOFs whose nodes display strong Lewis acidic character can hydrolyze such chemicals nearly instantaneously. However, without the help of a basic buffer to regenerate the active site, the benign organophosphorus product strongly binds to the node and prevents catalyst turnover. Here, we investigate a series of MOFs whose nodes contain metals of varying Lewis acidities and employ isothermal titration calorimetry (ITC) to directly measure the heat from the binding of an organophosphorus probe molecule, allowing the construction of a full thermodynamic binding profile (ΔH, ΔS, ΔG, K a ). We couple this with potentiometric titrations and solid state 31 P magic angle spinning (MAS) NMR to gain a clearer picture of how node identity, structure, and Lewis acidity interplay to impact binding strength and favorability. Furthermore, this study is the first to integrate these three complementary techniques to investigate binding interactions in MOFs, further showcasing the viability of ITC for probing MOF systems, which is still relatively underexplored.

Lewis acidity↗
NASA NTRS2002

Deciphering the Role of Desert Dust in the Climate Puzzle: The Mediterranean Israeli Dust Experiment (MEIDEX)

Numerous studies have shown that aerosol particles may be one of the primary agents that can offset the climate warming induced by the increase in the amount of atmospheric greenhouse gases. Desert aerosols are probably the most abundant and massive type of aerosol particles that are present in the atmosphere worldwide. These aerosols are carried over large distances and have various global impacts. They interact with clouds, impact the efficiency of their rain production and change their optical properties. They constitute one of the primary sources of minerals for oceanic life and influence the health of coral reefs. They have direct effects on human health, especially by inducing breathing difficulties in children. It was lately discovered that desert particles carry pathogens from the Sahara desert over the Atlantic Ocean, a fact that may explain the migration of certain types of diseases. Aerosols not only absorb solar radiation but also scatter it, so that their climatic effect is influenced not only by their physical properties and height distribution but also by the reflectivity of the underlying surface. This latter property changes greatly over land and is low over ocean surfaces. Aerosol plumes are emitted from discrete, sporadic sources in the desert areas of the world and are transported worldwide by the atmosphere's wind systems. For example, Saharan dust reaches Mexico City, Florida, Ireland, Switzerland and the Mediterranean region, while Asian dust reaches Alaska, Hawaii and the continental United States. This means that in order to assess its global effects, one must observe dust from space. The Space Shuttle is a unique platform, because it flies over the major deserts of our planet, enabling measurements and remote sensing of the aerosols as they travel from source to sink regions. Such efforts must always be accompanied by in-situ data for validation and calibration, with direct sampling of the airborne particles. MEIDEX is a joint project of the Israel Space Agency (ISA) and NASA, under a cooperation agreement between the two agencies.

Levin, Zev↗
NASA NTRS2005

Microbial Air and Surface Monitoring Results from International Space Station Samples

Over the course of long-duration spaceflight, spacecraft develop a microbial ecology that directly interacts with the crew of the vehicle. While most microorganisms are harmless or beneficial to the inhabitants of the vehicle, the presence of medically significant organisms appearing in this semi-closed environment could adversely affect crew health and performance. The risk of exposure of the crew to medically significant organisms during a mission is estimated using information gathered during nominal and contingency environmental monitoring. Analysis of the air and surface microbiota in the habitable compartments of the International Space Station (ISS) over the last four years indicate a high presence of Staphylococcus species reflecting the human inhabitants of the vehicle. Generally, air and surface microbial concentrations are below system design specifications, suggesting a lower risk of contact infection or biodegradation. An evaluation of sample frequency indicates a decrease in the identification of new species, suggesting a lower potential for unknown microorganisms to be identified. However, the opportunistic pathogen, Staphylococcus aureus, has been identified in 3 of the last 5 air samples and 5 of the last 9 surface samples. In addition, 47% of the coagulase negative Staphylococcus species that were isolated from the crew, ISS, and its hardware were found to be methicillin resistance. In combination, these observations suggest the potential of methicillin resistant infectious agents over time.

Ott, C. Mark↗
DOE OSTI2024

"Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test"

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. We explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

Jang, Kathy↗
DOE OSTI2024

Tritium Extraction from FLiBe using a Permeation Against Vacuum (PAV): Impact of Surface Potentials, Currents, and Coupling PAV to Sacrificial Anodes

Savannah River National Laboratory (SRNL) is exploring a concept of pairing a LiF-BeF2 (FLiBe) immersed Permeation Against Vacuum (PAV) tritium extraction system with a sacrificial anode. Several fusion concepts utilize FLiBe for tritium breeding, and breeding of tritium would occur from neutron interactions with the Li component, creating corrosive TF and/or T2. In absence of a redox buffered system, the TF would be able to attack containment materials until neutralized. One way to neutralize TF is to contact it with an active metal such as Be or Li which would preferentially combine with the fluorine in the TF to form BeF2 or LiF, respectively, and resulting in T2. When the active metal (e.g., Be) is oxidized, it will provide electrons, when T in TF is reduced and forms T2, it needs electrons. SRNL proposes to electrically link these two reactions and with the PAV to help drive the reactions faster than on their own and potentially increase T2 dissociation. In a soluble redox salt buffered system, it is expected that with sufficient buffering, T2, may form more rapidly and the core components would be more protected, but the soluble redox salt buffer would need to be occasionally regenerated, which could be accomplished by again contacting the salt with an active metal such as Be or Li, although in this case the cathodic reaction would be electrons coming from the shift in oxidative state of the redox buffer. The exploration of potential and current effects on the PAV and impacts of redox agents will be discussed.

Olson, Luke C.↗
DOE OSTI2025

Reinforcement Learning-Based Oscillation Dampening: Scaling Up Single-Agent Reinforcement Learning Algorithms to a 100-Autonomous-Vehicle Highway Field Operational Test

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. Here, we explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Range-wide population assessments for subalpine fir indicate widespread disturbance-driven decline

Subalpine forests in western North America are threatened by rapid climate change, increased activity by endemic and exotic insects and diseases, and changing wildfire regimes. The interactive effects of these stressors have resulted in pronounced population declines in many subalpine tree species; however, a systematic assessment of the status and trends of subalpine forests is lacking. Subalpine fir (Abies lasiocarpa) is a widespread species across the western United States, with documented population declines in many parts of its distribution. Here we use subalpine fir as an initial leverage point to build a more complete understanding of subalpine forest baseline conditions and responses to environmental change. Specifically, we leverage the USDA Forest Service Forest Inventory and Analysis (FIA) database to (1) ask how subalpine fir populations are changing across the species’ distribution in the western US, (2) assess the drivers of recent subalpine fir population trends, and (3) explore whether those changes imply generalized species-wide and/or system-wide decline. We found that subalpine fir abundance and basal area are declining concurrently across ~ 62% of the species’ distribution, and increasing across ~ 19%. Range-wide, we estimated 25.02 ± 2.74 % subalpine fir mortality between 2000 and 2009 and 2010–2019 FIA inventory periods, with higher mortality concentrated in the eastern Oregon Cascades, central Idaho, and parts of southern Colorado. High regeneration density did not predict positive population trajectories, which were instead associated with higher rates of adult recruitment. While the importance of different mortality agents varied substantially between ecoregions, 83.4% of total range-wide mortality was related to fire or biological disturbance. Declining subalpine fir basal area coincided with declines in the basal area of other co-occurring tree species in 39% of subalpine forest area, and with increases in conspecific basal area in 22% of forest area. Fire disturbance was the single largest cause of subalpine fir mortality; however, even where subalpine fir fire mortality was high, mortality among other species was primarily caused by insects. In conclusion, our results suggest that subalpine fir declines across large portions of the western United States are driven by forest disturbance, and that declines in subalpine fir populations may be indicative of negative change in subalpine forest systems broadly.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Bioinformatic and Mechanistic Analysis of the Palmerolide PKS-NRPS Biosynthetic Pathway From the Microbiome of an Antarctic Ascidian

Complex interactions exist between microbiomes and their hosts. Increasingly, defensive metabolites that have been attributed to host biosynthetic capability are now being recognized as products of host-associated microbes. These unique metabolites often have bioactivity targets in human disease and can be purposed as pharmaceuticals. Polyketides are a complex family of natural products that often serve as defensive metabolites for competitive or pro-survival purposes for the producing organism, while demonstrating bioactivity in human diseases as cholesterol lowering agents, anti-infectives, and anti-tumor agents. Marine invertebrates and microbes are a rich source of polyketides. Palmerolide A, a polyketide isolated from the Antarctic ascidian Synoicum adareanum, is a vacuolar-ATPase inhibitor with potent bioactivity against melanoma cell lines. The biosynthetic gene clusters (BGCs) responsible for production of secondary metabolites are encoded in the genomes of the producers as discrete genomic elements. A candidate palmerolide BGC was identified from a S. adareanum microbiome-metagenome based on a high degree of congruence with a chemical structure-based retrobiosynthetic prediction. Protein family homology analysis, conserved domain searches, active site and motif identification were used to identify and propose the function of the ~75 kbp trans-acyltransferase (AT) polyketide synthase-non-ribosomal synthase (PKS-NRPS) domains responsible for the stepwise synthesis of palmerolide A. Though PKS systems often act in a predictable co-linear sequence, this BGC includes multiple trans-acting enzymatic domains, a non-canonical condensation termination domain, a bacterial luciferase-like monooxygenase (LLM), and is found in multiple copies within the metagenome-assembled genome (MAG). Detailed inspection of the five highly similar pal BGC copies suggests the potential for biosynthesis of other members of the palmerolide chemical family. This is the first delineation of a biosynthetic gene cluster from an Antarctic microbial species, recently proposed as Candidatus Synoicihabitans palmerolidicus. These findings have relevance for fundamental knowledge of PKS combinatorial biosynthesis and could enhance drug development efforts of palmerolide A through heterologous gene expression.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1982

Bethanechol-Induced Water Intake in Rats: Possible Mechanisms of Induction

Acute administration of the parasympathomimetic agent, bethanechol, at 2, 4, 8 and 12 mg/kg body wt, IP, induced drinking and increased urine output of rats in a dose-dependent fashion. The first significant increases in both water intake and urine output above that of controls occurred when 4 mg/kg was administered. The drinking and increased urine output in response to administration of 8 mg bethanechol/kg was inhibited by atropine sulfate (3 and 6 mg/kg, IP). In addition, the 0-adrenergic antagonist, propranolol (6 mg/kg, IP, administered 30 min prior to treatment with bethanechol), inhibited bethanechol (8 mg/kg, IP)-induced drinking. Urine output, however, was unaffected by propranolol. Further, the angiotensin I converting enzyme inhibitor, captopril, inhibited significantly the drinking response, but not the increased urine output, accompanying administration of bethanechol (8 mg/kg). The effect of bethanechol and the beta-adrenergic agonist, isoproterenol (25 Ag/kg) separately and in combination, on water intake was also studied. Both compounds increased water intake but they exerted no interactive effect when administered simultaneously. Administration of bethanechol (8 mg/kg) to conscious rats was also accompanied by a significant reduction in both mean blood pressure and heart rate that reached minimal levels within 10 min after treatment. Both responses had returned to control level by one hour after treatment. These results suggest that bethanechol induces drinking in rats by way of the renin-angiotensin system.

Fregly, Melvin J.↗
NASA NTRS2012

Impact of Aerosols on Convective Clouds and Precipitation

Aerosols are a critical factor in the atmospheric hydrological cycle and radiation budget. As a major agent for clouds to form and a significant attenuator of solar radiation, aerosols affect climate in several ways. Current research suggests that aerosol effects on clouds could further extend to precipitation, both through the formation of cloud particles and by exerting persistent radiative forcing on the climate system that disturbs dynamics. However, the various mechanisms behind these effects, in particular the ones connected to precipitation, are not yet well understood. The atmospheric and climate communities have long been working to gain a better grasp of these critical effects and hence to reduce the significant uncertainties in climate prediction resulting from such a lack of adequate knowledge. Here we review past efforts and summarize our current understanding of the effect of aerosols on convective precipitation processes from theoretical analysis of microphysics, observational evidence, and a range of numerical model simulations. In addition, the discrepancy between results simulated by models, as well as that between simulations and observations, are presented. Specifically, this paper addresses the following topics: (1) fundamental theories of aerosol effects on microphysics and precipitation processes, (2) observational evidence of the effect of aerosols on precipitation processes, (3) signatures of the aerosol impact on precipitation from largescale analyses, (4) results from cloud-resolving model simulations, and (5) results from large-scale numerical model simulations. Finally, several future research directions for gaining a better understanding of aerosol--cloud-precipitation interactions are suggested.

Tao, Wei-Kuo↗
NASA NTRS1997

A Cognitive System Model for Human/Automation Dynamics in Airspace Management

NASA has initiated a significant thrust of research and development focused on providing the flight crew and air traffic managers automation aids to increase capacity in en route and terminal area operations through the use of flexible, more fuel-efficient routing, while improving the level of safety in commercial carrier operations. In that system development, definition of cognitive requirements for integrated multi-operator dynamic aiding systems is fundamental. In order to support that cognitive function definition, we have extended the Man Machine Integrated Design and Analysis System (MIDAS) to include representation of multiple cognitive agents (both human operators and intelligent aiding systems) operating aircraft, airline operations centers and air traffic control centers in the evolving airspace. The demands of this application require representation of many intelligent agents sharing world-models, and coordinating action/intention with cooperative scheduling of goals and actions in a potentially unpredictable world of operations. The MIDAS operator models have undergone significant development in order to understand the requirements for operator aiding and the impact of that aiding in the complex nondeterminate system of national airspace operations. The operator model's structure has been modified to include attention functions, action priority, and situation assessment. The cognitive function model has been expanded to include working memory operations including retrieval from long-term store, interference, visual-motor and verbal articulatory loop functions, and time-based losses. The operator's activity structures have been developed to include prioritization and interruption of multiple parallel activities among multiple operators, to provide for anticipation (knowledge of the intention and action of remote operators), and to respond to failures of the system and other operators in the system in situation-specific paradigms. The model's internal representation has been be modified so that multiple, autonomous sets of equipment will function in a scenario as the single equipment sets do now. In order to support the analysis requirements with multiple items of equipment, it is necessary for equipment to access the state of other equipment objects at initialization time (a radar object may need to access the position and speed of aircraft in its area, for example), and as a function of perception and sensor system interaction. The model has been improved to include multiple world-states as a function of equipment am operator interaction. The model has been used -1o predict the impact of warning and alert zones in aircraft operation, and, more critic-ally, the interaction of flight-deck based warning mechanisms and air traffic controller action in response to ground-based conflict prediction and alerting systems. In this operation, two operating systems provide alerting to two autonomous, but linked sets of operators, whose view of the system and whose dynamics in response are radically different. System stability and operator action was predicted using the MIDAS model.

Corker, Kevin M.↗
NASA NTRS2004

A Multiagent Modeling Environment for Simulating Work Practice in Organizations

In this paper we position Brahms as a tool for simulating organizational processes. Brahms is a modeling and simulation environment for analyzing human work practice, and for using such models to develop intelligent software agents to support the work practice in organizations. Brahms is the result of more than ten years of research at the Institute for Research on Learning (IRL), NYNEX Science & Technology (the former R&D institute of the Baby Bell telephone company in New York, now Verizon), and for the last six years at NASA Ames Research Center, in the Work Systems Design and Evaluation group, part of the Computational Sciences Division (Code IC). Brahms has been used on more than ten modeling and simulation research projects, and recently has been used as a distributed multiagent development environment for developing work practice support tools for human in-situ science exploration on planetary surfaces, in particular a human mission to Mars. Brahms was originally conceived of as a business process modeling and simulation tool that incorporates the social systems of work, by illuminating how formal process flow descriptions relate to people s actual located activities in the workplace. Our research started in the early nineties as a reaction to experiences with work process modeling and simulation . Although an effective tool for convincing management of the potential cost-savings of the newly designed work processes, the modeling and simulation environment was only able to describe work as a normative workflow. However, the social systems, uncovered in work practices studied by the design team played a significant role in how work actually got done-actual lived work. Multi- tasking, informal assistance and circumstantial work interactions could not easily be represented in a tool with a strict workflow modeling paradigm. In response, we began to develop a tool that would have the benefits of work process modeling and simulation, but be distinctively able to represent the relations of people, locations, systems, artifacts, communication and information content.

Sierhuis, Maarten↗
NASA NTRS2010

Filovirus Research: The Need for an Integrated Approach in Time and Space

The episodic appearance of Ebola virus (EBOV) and Marburg virus (MARV) across central Africa over the last 15 years not only underscores the importance of filoviruses as uniquely virulent agents to both human and wildlife communities but also implies a very complex transmission scenario that must be understood if we are to prevent or mitigate filovirus outbreaks in the future. Efforts of a global network of scientists and healthcare workers have expanded our knowledge of filoviruses to meet the growing threat of Ebola and Marburg hemorrhagic fevers in Africa. In recent decades, several newly emerging diseases have resulted in major threats to both affected communities and global public health. Viruses from wildlife hosts in particular, have exhibited a capability for cross-species transmission (CST), and have caused high-impact diseases in humans Such as Ebola and Marburg hemorrhagic fevers, Nipah and severe acute respiratory syndrome (SAILS). It has been estimated that about 60.3% (Jones et al. 2008) of human infectious diseases are of animal origin (zoonoses) and even some important viral diseases that are traditionally considered of human origin, for example measles and smallpox, may very well have their prehistoric origins in wildlife (Wolfe et al 2007). It maybe logical and prudent therefore, to anticipate that there are other, new filoviruses out there that will cross into humans at some point in time. If we anticipate that these will happen and wish to be prepared for and mitigate this potential, then an understanding of filoviruses as a biologic system in the environment will be essential to that process. We will need to know how the ecological dynamic of CST interacts with a 'new' viruse's evolutionary factors to overcome environmental, demographic and host-specific barriers to transmission and infectivity to humans.

Pinzon, Jorge E.↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2020

Sea Level Rise in the CESM Large Ensemble: The Role of Individual Climate Forcings and Consequences for the Coming Decades

The emergence of a spatial pattern in the externally forced response (FR) of dynamic sea level (DSL) during the altimeter era has recently been demonstrated using climate models but our understanding of its initial emergence, drivers, and implications for the future is poor. Here the anthropogenic forcings of the DSL pattern are explored using the Community Earth System Model Large Ensemble (CESM-LE) and Single-Forcing Large Ensemble, a newly available set of simulations where values of individual forcing agents remain fixed at 1920 levels, allowing for an estimation of their effects. Statistically significant contributions to the DSL FR are identified for greenhouse gases (GHGs) and industrial aerosols (AERs), with particularly strong contributions resulting from AERs in the mid-twentieth century and GHGs in the late twentieth and twenty-first century. Secondary, but important, contributions are identified for biomass burning aerosols in the equatorial Atlantic Ocean in the mid-twentieth century, and for stratospheric ozone in the Southern Ocean during the late twentieth century. Key to understanding regional DSL patterns are ocean heat content and salinity anomalies, which are driven by surface heat and freshwater fluxes, ocean dynamics, and the spatial structure of seawater thermal expansivity. Finally, potential implications for the interpretation of DSL during the satellite era and the longer records from tide gauges are suggested as a topic for future research.

54 ENVIRONMENTAL SCIENCES↗