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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.

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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

MESA: Scalable Runtime Verification Tool Using Actors

This work presents our runtime verification approach implemented by the tool MESA (MEssage-based System Analysis) which allows for using concurrent monitors to check for properties specified in linear temporal logic and finite state machines.We employ the actor programing model to implement MESA where monitors are captured by concurrent actors that communicate via messaging. The paper also presents a case study where MESA is used to monitor flights in National Airspace System of United States using live air traffic data stream. The case study which motivated this work in the first place shows that our approach is effective.We also perform empirical study by conducting experiments using monitoring systems with different numbers of concurrent monitors and different layers of indexing.This paper describes our experiments, evaluates our results,and discusses challenges faced during the study. The evaluation shows our approach is scalable.

runtime verification, concurrency, actor programin↗
NASA NTRSDate not supplied

Actor-based Runtime Verification with MESA

This work presents a runtime verification approach implemented in the tool MESA (MEssage-based System Analysis) which allows for using concurrent monitors to check for properties specified in data parameterized temporal logic and state machines. The tool is implemented as an internal Scala DSL. We employ the actor programming model to implement MESA where monitors are captured by concurrent actors that communicate via messaging. The paper presents a case study in which MESA is used to effectively monitor a large number of flights from live US airspace data streams. We also perform an empirical study by conducting experiments using monitoring systems with different numbers of concurrent monitors and different layers of indexing on the data contained in events. The paper describes the experiments, evaluates the results, and discusses challenges faced during the study. The evaluation shows the value of combining concurrency with indexing to handle data rich events.

runtime verification↗
NASA NTRS1998

Performance Analysis of an Actor-Based Distributed Simulation

Object-oriented design of simulation programs appears to be very attractive because of the natural association of components in the simulated system with objects. There is great potential in distributing the simulation across several computers for the purpose of parallel computation and its consequent handling of larger problems in less elapsed time. One approach to such a design is to use "actors", that is, active objects with their own thread of control. Because these objects execute concurrently, communication is via messages. This is in contrast to an object-oriented design using passive objects where communication between objects is via method calls (direct calls when they are in the same address space and remote procedure calls when they are in different address spaces or different machines). This paper describes a performance analysis program for the evaluation of a design for distributed simulations based upon actors.

Schoeffler, James D.↗
NASA NTRS2020

Actor-based Runtime Verification with MESA

This work presents a runtime verification approach implemented in the tool MESA (MEssage-based System Analysis) which allows for using concurrent monitors to check for properties specified in data parameterized temporal logic and state machines. The tool is implemented as an internal Scala DSL. We employ the actor programming model to implement MESA where monitors are captured by concurrent actors that communicate via messaging. The paper presents a case study in which MESA is used to effectively monitor a large number of flights from live US airspace data streams. We also perform an empirical study by conducting experiments using monitoring systems with different num- bers of concurrent monitors and different layers of indexing on the data contained in events. The paper describes the experiments, evaluates the results, and discusses challenges faced during the study. The evaluation shows the value of combining concurrency with indexing to handle data rich events.

Mehlitz, Peter↗
DOE OSTI2024

Scenario storyline discovery for complex multi-actor human-natural systems

This poster was presented at the AGU Fall Meeting 2024. Abstract:Scenario analysis is a useful tool for assessing the impacts of future conditions or alternative strategies. However, the common practice of focusing on a small number of predetermined scenarios can limit our understanding of key uncertainties, and fail to represent diverse stakeholder impacts. Exploratory modeling approaches have been developed to address these issues by simulating a wide range of possible futures and system perspectives. A challenge with these approaches is that they often involve large ensemble experiments which limit interpretability and usability. We recently introduced the FRamework for Narrative Storylines and Impact Classification (FRNSIC; pronounced ``forensic''), a scenario discovery framework that helps users identify scenario storylines that capture key system dynamics and as well as important outcomes. In this poster presentation, we present training materials to support the generalizable application of the framework to other multi-actor systems with complex dynamics. Specifically, we will present a step-by-step methodological typology of tools and methods that can be used to generate and classify plausible states of the world on key metrics and consequential dynamics. The typology will also discuss potential implications of these choices and their applicability to different systems.

Colorado River↗
NASA NTRS1985

Performance evaluation of a simulated data-flow computer with low-resolution actors

Basic problems related to the exploitation of parallelism in a program include sequencing of the instructions and communication of the data. It is pointed out that the data-flow approach offers an elegant solution to the sequencing problem, since all data dependencies are automatically handled and only instructions with ready input sets are activated. It is shown that a change in the level of subcomputations (actors) affects communications costs. The concept of variable resolution is discussed, and the testbed environment is examined. Attention is given to the architecture of the processing elements, the communication network, and the simulators. A description of the analytical model is also provided. Simulation and results are discussed, taking into account test programs and allocation, the variation of the number of processing elements, the variation of the resolution in directed acyclic graphs, performance in processing loops, and array handling.

Gaudiot, J. L.↗
DOE OSTI2025

MSD CoP Webinar: "Generative agents: A new frontier for representing human actors and their behavior in MSD models"

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Talk #1: Behavioral Generative Agents for Energy Operations Presenter: Dr. Cong Chen (Thayer School of Engineering, Dartmouth College) Abstract: Accurately modeling consumer behavior in energy operations remains challenging due to inherent uncertainties, behavioral complexities, and limited empirical data. This talk introduces a novel approach leveraging generative agents--artificial agents powered by large language models--to realistically simulate customer decision-making in dynamic energy operations. Talk #2: Simulating multiple human perspectives in socio-ecological systems using large language models Presenter: Dr. Yongchao Zeng (Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU) of the Karlsruhe Institute of Technology in Germany) Abstract: Understanding socio-ecological systems requires insights from diverse stakeholder perspectives. This talk describes a novel simulation system called HoPeS (Human-oriented Perspective Shifting). HoPeS enables model users to not only explore simulated socio-ecological systems (SESs) from a third-person observer's perspective but also take any of the simulated stakeholder roles, like playing an RPG game. By shifting multiple perspectives, model users can reflect and integrate the situated knowledge learned through the participatory simulation, approximating a more holistic and less biased understanding of SESs. Moderators: Jim Yoon (MSD CoP Human Systems Modeling Working Group Co-Chair); Stefano Galelli (MSD CoP Using AI to Enhance MSD Research Working Group Co-Chair); Patrick M. Reed (MSD CoP Facilitation Team) This webinar was held on: November 13th, 2025 from 12-1 PM EST.

Artificial Intelligence↗
NASA NTRS1994

A workout for virtual bodybuilders (design issues for embodiment in multi-actor virtual environments)

This paper explores the issue of user embodiment within collaborative virtual environments. By user embodiment we mean the provision of users with appropriate body images so as to represent them to others and also to themselves. By collaborative virtual environments we mean multi-user virtual reality systems which support cooperative work (although we argue that the results of our exploration may also be applied to other kinds of collaborative systems). The main part of the paper identifies a list of embodiment design issues including: presence, location, identity, activity, availability, history of activity, viewpoint, action point, gesture, facial expression, voluntary versus involuntary expression, degree of presence, reflecting capabilities, manipulating the user's view of others, representation across multiple media, autonomous and distributed body parts, truthfulness and efficiency. Following this, we show how these issues are reflected in our own DIVE and MASSIVE prototype collaborative virtual environments.

Benford, Steve↗
NASA NTRS2016

RACE: Building Airspace Simulations Faster and Better with Actors

Large, distributed aerospace simulations traditionally have been the domain of customized, closed designs, using statically compiled code based on specialized messaging systems such as DDS and HLA. While this can be suitable for one-off systems or specialized in-house product lines, it increases development costs and lowers extensibility. We propose to use contemporary internet software technology to solve this problem.Our Runtime for Airspace Concept Evaluation (RACE) architecture was born out of the need to rapidly develop and evaluate what-if scenarios that involve the whole National Airspace System (NAS), live NAS data feeds such as the FAA's System Wide Information Management (SWIM) servers, and existing flight simulators. It had to run on off-the-shelf hardware, be open sourced, and support visualization components up to multiple synchronized large screen geo viewers used in situation rooms. Most of all, it had to be extensible - being a viable platform for the development of future simulation components.

Mehlitz, Peter↗
NASA NTRS1986

Ada and knowledge-based systems: A prototype combining the best of both worlds

A software architecture is described which facilitates the construction of distributed expert systems using Ada and selected knowledge based systems. This architecture was utilized in the development of a Knowledge-based Maintenance Expert System (KNOMES) prototype for the Space Station Mobile Service Center (MSC). The KNOMES prototype monitors a simulated data stream from MSC sensors and built-in test equipment. It detects anomalies in the data and performs diagnosis to determine the cause. The software architecture which supports the KNOMES prototype allows for the monitoring and diagnosis tasks to be performed concurrently. The basic concept of this software architecture is named ACTOR (Ada Cognitive Task ORganization Scheme). An individual ACTOR is a modular software unit which contains both standard data processing and artificial intelligence components. A generic ACTOR module contains Ada packages for communicating with other ACTORs and accessing various data sources. The knowledge based component of an ACTOR determines the role it will play in a system. In this prototype, an ACTOR will monitor the MSC data stream.

Brauer, David C.↗
NASA NTRS1997

The Application of New Software Technology to the Architecture of the National Cycle Program

As part of the Numerical Propulsion System Simulation (NPSS) effort of NASA Lewis in conjunction with the United States aeropropulsion industry, a new system simulation framework, the National Cycle Program (NCP), capable of combining existing empirical engine models with new detailed component-based computational models is being developed. The software architecture of the NCP program involves a generalized object- oriented framework and a base-set of engine component models along with supporting tool kits which will support engine simulation in a distributed environment. As the models are extended to contain two and three dimensions the computing load increases rapidly and it is intended that this load be distributed across multiple work stations executing concurrently in order to get acceptably fast results. The research carried out was directed toward performance analysis of the distributed object system. More specifically, the performance of the actor-based distributed object design I created earlier was desired. To this end, the research was directed toward the design and implementation of suitable performance-analysis techniques and software to demonstrate those techniques. There were three specific results which are reported in two separate reports submitted separately as NASA Technical Memoranda. The results are: (1) Design, implementation, and testing of a performance analysis program for a set of active objects (actor based objects) which allowed the individual actors to be assigned to arbitrary processes on an arbitrary set of machines. (2) The global-balance-equation approach has the fundamental limitation that the number of equations increases exponentially with the number of actors. Hence, unlike many approximate approaches to this problem, the nearest-neighbor approach allows checking of the solution and an estimate of the error. The technique was demonstrated in a prototype analysis program as part of this research. The results of the program were checked against the global-balance solution discussed above. Late during the grant, a much better approximation was developed and this is discussed in result below. As a consequence, a proposal was submitted to continue the research by developing the new approximation including development of a complete program from the prototype. (3) The source of approximation in the nearest-neighbor algorithm is the requirement for estimating some joint probabilities from some marginal distributions. A completely ad hoc estimate was used in the prototype.

Schoeffler, James D.↗
NASA NTRS2014

Multiple Pathways of Commodity Crop Expansion in Tropical Forest Landscapes

Commodity crop expansion, for both global and domestic urban markets, follows multiple land change pathways entailing direct and indirect deforestation, and results in various social and environmental impacts. Here we compare six published case studies of rapid commodity crop expansion within forested tropical regions. Across cases, between 1.7 percent and 89.5 percent of new commodity cropland was sourced from forestlands. Four main factors controlled pathways of commodity crop expansion: (i) the availability of suitable forestland, which is determined by forest area, agroecological or accessibility constraints, and land use policies, (ii) economic and technical characteristics of agricultural systems, (iii) differences in constraints and strategies between small-scale and large-scale actors, and (iv) variable costs and benefits of forest clearing. When remaining forests were unsuitable for agriculture and/or policies restricted forest encroachment, a larger share of commodity crop expansion occurred by conversion of existing agricultural lands, and land use displacement was smaller. Expansion strategies of large-scale actors emerge from context-specific balances between the search for suitable lands; transaction costs or conflicts associated with expanding into forests or other state-owned lands versus smallholder lands; net benefits of forest clearing; and greater access to infrastructure in already cleared lands. We propose five hypotheses to be tested in further studies: (i) land availability mediates expansion pathways and the likelihood that land use is displaced to distant, rather than to local places; (ii) use of already-cleared lands is favored when commodity crops require access to infrastructure; (iii) in proportion to total agricultural expansion, large-scale actors generate more clearing of mature forests than smallholders; (iv) property rights and land tenure security influence the actors participating in commodity crop expansion, the form of land use displacement, and livelihood outcomes; (v) intensive commodity crops may fail to spare land when inducing displacement. We conclude that understanding pathways of commodity crop expansion is essential to improve land use governance.

Forest↗
NASA NTRS2021

Concurrent Runtime Verification of Data Rich Events

This paper presents the open source runtime verification tool MESA (MEssage-based System Analysis), implemented in Scala, which supports concurrent monitors using the Actor model. Furthermore, the tool supports indexing (slicing) on the data values occurring in data-carrying events, for each individual monitor. The tool is generic in the sense that any monitoring system can be used for creating monitors. In this paper, we use the internal Scala DSL Daut for programming such in data parameterized state machines and temporal logic. To illustrate MESA/Daut, we present a case study that monitors flights from live U.S. airspace data streams, verifying that they conform to planned routes. With base in the case study, we then perform an extensive empirical study of the potential benefits from monitoring slices of a single property in concurrently executing actors. Due to the overhead of scheduling “small” actors (one for each slice or a small number of slices), it is not obvious that concurrent execution of such is beneficial. However, as a main result, we demonstrate that concurrent monitoring of slices to handle data-carrying events can provide considerable speed gains.

finite state machines↗
NASA NTRS2010

Collective Intelligence and Three Aspects of Planning in Organizations: A NASA Example

For many complex sociotechnical systems, planning seems to require explicit coordination; certainly, in executing a plan the activities of different actors must be tightly coupled. However, distributing the needed planning information can be very burdensome and error prone, because different groups need different collections of information, updated or kept current on different time cycles. Further, the information needed to form successful plans is often highly distributed, and while feedback about the success of prior plans may exist, it may not be available to those in a position of using this to improve plans or to detect and resolve other problems in the system (Weick, 1995). Tools to support various aspects of planning have been developed, and can provide a huge benefit to the individuals working on that aspect. To be tractable, most solutions address a quite bounded slice of work, isolating it from the larger context. Prospective planning takes place over multiple, nested cycles of decision making. This builds a plan that specifies activities of different granularity. "Subplans" may specify multiple parallel activities by different groups and individuals, as well as sequential, nested actions by a single actor. Planning produces valuable, sharable, external, representations: in addition to prospective use, plans support retrospective assessment and also action in the present. Viewing planning in a larger context - both temporal and organizational -- enables noticing what one does not know and generating more systemic and effective solutions. Viewing a problem as one of collective intelligence invites thinking about the larger organizational context. Many approaches to supporting collective intelligence do not support execution of highly contingent actions, distributed across many players, and hence provide incomplete support for planning. However, CI technology maybe helpful in managing the processes of gathering information for decision making in planning and of distributing plan information to various actors, needed on various time cycles.

Billman, Dorrit↗
NASA NTRS2012

Transcendental Political Systems and the Gravity Model

This summer I have been working on an Army Deep Futures Model project named Themis. Themis is a JPL based modeling framework that anticipates possible future states for the world within the next 25 years. The goal of this framework is to determine the likelihood that the US Army will need to intervene on behalf of the US strategic interests. Key elements that are modeled within this tool include the world structure and major decisions that are made by key actors. Each actor makes decisions based on their goals and within the constraints of the structure of the system in which they are located. In my research I have focused primarily on the effects of structures upon the decision-making processes of the actors within them. This research is a natural extension of my major program at Georgetown University, where I am studying the International Political Economy and the structures that make it up. My basic goal for this summer project was to be a helpful asset to the Themis modeling team, with any research done or processes learned constituting a bonus.

Army Deep Futures Model↗
NASA NTRS2015

A Fast Goal Recognition Technique Based on Interaction Estimates

Goal Recognition is the task of inferring an actor's goals given some or all of the actor's observed actions. There is considerable interest in Goal Recognition for use in intelligent personal assistants, smart environments, intelligent tutoring systems, and monitoring user's needs. In much of this work, the actor's observed actions are compared against a generated library of plans. Recent work by Ramirez and Geffner makes use of AI planning to determine how closely a sequence of observed actions matches plans for each possible goal. For each goal, this is done by comparing the cost of a plan for that goal with the cost of a plan for that goal that includes the observed actions. This approach yields useful rankings, but is impractical for real-time goal recognition in large domains because of the computational expense of constructing plans for each possible goal. In this paper, we introduce an approach that propagates cost and interaction information in a plan graph, and uses this information to estimate goal probabilities. We show that this approach is much faster, but still yields high quality results.

gola recognition↗
NASA NTRSDate not supplied

Informing New Concepts for UAS and Autonomous System Safety Management using Disaster Management and First Responder Scenarios

As emerging flight operations become more prevalent and increasingly automated and distributed, the capabilities for managing safety of vehicles and operations will also need to evolve. To address this challenge, the National Academies has envisioned an In-Time Aviation Safety Management System (IASMS) capability for a wide range of aviation operations including current commercial operations as well as new entrants envisioned with advanced air mobility (AAM). The suite of IASMS services, functions, and capabilities (SFCs) would be implemented in a federated approach and would address trends as well as individual operations. Through predictive modeling and data analysis, IASMS is envisioned to identify arising risks so that they can be mitigated, in-time, before a safety incident occurs. IASMS and its requisite set of SFCs must leverage a wide range of information to perform. To better understand these new needs, FSF worked with the aviation and humanitarian communities to develop and validate scenarios that include traditional aviation operations and UAS operations intermingled as they are deployed for disaster management and first responder (DMFR) situations. The three scenarios developed include: • Post Natural disaster response, such as a hurricane, involving multiple parties utilizing traditional aviation and UAS to support rescue operations, surveil damage, and locate survivors needing assistance. • Wildfire fighting in remote locations with traditional aircraft for transport and fire-retardant delivery combined with UAS for surveillance of fire locations as well as to track individual firefighter locations. • Medical Operations and AAM in Urban Environments including passenger-carrying helicopters and AAM vehicles, medical missions (such as transport of radio-pharmaceuticals), and other UAS delivery operations (such as the delivery of defibrillators). Each scenario was developed and validated by representatives with expertise in humanitarian operations, urban and rural emergency response, air traffic management, UAS operations, and traditional flight operations. The scenario definitions address roles and responsibilities of individual actors, the appropriate utilization of UAS, and the actions taken by those actors to appropriately manage risks associated with the mission and environment. The risks to aviation traffic and to people on the ground explored included potential risks arising from incompatibilities in calculating reference altitudes (eg, differing uses of AGL, MSL, barometric, or GPS-derived values), loss of command and control (C2) communications, rapid changes in weather and winds, and physical interference. For each risk, IASMS SFCs were postulated in the context of monitoring services, risk assessment capabilities, and identifying appropriate mitigation strategies. The identified SFC capabilities were envisioned from known services postulated for IASMS and for UTM. For these unique environments, IASMS SFCs are needed to address conditions such as hazardous payloads, micro-climates and urban canyons, and the need to keep uninvolved air traffic out of the area where DMFR operations are being conducted. The second phase of analysis focused on inferring the specific information needs and the SFCs for IASMS, utilizing a structure of 16 information classes to organize requirements. For each of the risks identified in the workshops, it was postulated what data sources would be necessary to monitor critical aspects of the risk (eg, surrounding air traffic, ground population, terrain, etc). to be directly measured as well as data that would be derived, which implies additional SFCs for different actors to understand what information would likely be exchanged between parties. For an IASMS to be effective, additional research is needed to develop the advanced algorithms that can address the increasingly autonomous and complex operations in differing environments and to develop means of identifying unknown risks. Looking at these scenarios highlighted a number of research issues. These include the ability to quickly "cordon off" airspace thru temporary flight restrictions (TFRs) or other means, developing clear definitions to enable automation-based algorithms for prioritizing operations, defining airspace density metrics, standardization of altitude reporting, and establishing a basis for safety data metrics definition and collection. This paper seeks to outline the development of an IASMS in the context of the DMFR scenarios and resulting demonstrations. Utilizing this contextual approach, NASA will generate recommendations for an assured safety framework for AAM operations that enables AAM operations to safely access the NAS.

In Time Aviation Safety Management System↗