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NASA NTRS2004

Model of a Piezoelectric Transducer

It's difficult to control liquid and gas in propellant tanks in zero gravity. A possible a design would utilize acoustic liquid manipulation (ALM) technology which uses ultrasonic beams conducted through a liquid and solid media, to push gas bubbles in the liquid to desirable locations. We can propel and control the bubble with acoustic radiation pressure by aiming the acoustic waves on the bubble s surface. This allows us to design a so called smart tank in which the ALM devices transfer the gas to the outer wall of the tank and isolating the liquid in the center. Because the heat transfer rate of a gas is lower of that of the liquid it would substantially decrease boil off and provide of for a longer storage life. The ALM beam is composed of little wavelets which are individual waves that constructively interfere with each other to produce a single, combined acoustic wave front. This is accomplished by using a set of synchronized ultrasound transducers arranged in an array. A slight phase offset of these elements allows us to focus and steer the beam. The device that we are using to produce the acoustic beam is called the piezoelectric transducer. This device converts electrical energy to mechanical energy, which appears in the form of acoustic energy. Therefore the behavior of the device is dependent on both the mechanical characteristics, such as its density, cross-sectional area, and its electrical characteristics, such as, electric flux permittivity and coupling factor. These devices can also be set up in a number of modes which are determined by the way the piezoelectric device is arranged, and the shape of the transducer. For this application we are using the longitudinal or thickness mode for our operation. The transducer also vibrates in the lateral mode, and one of the goals of my project is to decrease the amount of energy lost to the lateral mode. To model the behavior of the transducers I will be using Pspice, electric circuit modeling tool, to determine the transducer's electrical characteristics at the frequency of interest. This will also help me determine the characteristics of an impedance matching network to operate the transducer at its optimum efficiency. For this I will use ABMs (analog behavioral modeling) to model dependent current and voltage sources that represent the transducer. I have also been working on the Labview control software for the phased array used to control the bubbles, and will begin testing on that before the end of my internship.

Goodenow, Debra↗

NASA NTRS2009

Complexity Science Applications to Dynamic Trajectory Management: Research Strategies

The promise of the Next Generation Air Transportation System (NextGen) is strongly tied to the concept of trajectory-based operations in the national airspace system. Existing efforts to develop trajectory management concepts are largely focused on individual trajectories, optimized independently, then de-conflicted among each other, and individually re-optimized, as possible. The benefits in capacity, fuel, and time are valuable, though perhaps could be greater through alternative strategies. The concept of agent-based trajectories offers a strategy for automation of simultaneous multiple trajectory management. The anticipated result of the strategy would be dynamic management of multiple trajectories with interacting and interdependent outcomes that satisfy multiple, conflicting constraints. These constraints would include the business case for operators, the capacity case for the Air Navigation Service Provider (ANSP), and the environmental case for noise and emissions. The benefits in capacity, fuel, and time might be improved over those possible under individual trajectory management approaches. The proposed approach relies on computational agent-based modeling (ABM), combinatorial mathematics, as well as application of "traffic physics" concepts to the challenge, and modeling and simulation capabilities. The proposed strategy could support transforming air traffic control from managing individual aircraft behaviors to managing systemic behavior of air traffic in the NAS. A system built on the approach could provide the ability to know when regions of airspace approach being "full," that is, having non-viable local solution space for optimizing trajectories in advance.

Sawhill, Bruce↗

NASA NTRS2010

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

Shameldin, Ramez Ahmed↗

NASA NTRS2011

Modeling Being "Lost": Imperfect Situation Awareness

Being "lost" is an exemplar of imperfect Situation Awareness/Situation Understanding (SA/SU) -- information/knowledge that is uncertain, incomplete, and/or just wrong. Being "lost" may be a geo-spatial condition - not knowing/being wrong about where to go or how to get there. More broadly, being "lost" can serve as a metaphor for uncertainty and/or inaccuracy - not knowing/being wrong about how one fits into a larger world view, what one wants to do, or how to do it. This paper discusses using agent based modeling (ABM) to explore imperfect SA/SU, simulating geo-spatially "lost" intelligent agents trying to navigate in a virtual world. Each agent has a unique "mental map" -- its idiosyncratic view of its geo-spatial environment. Its decisions are based on this idiosyncratic view, but behavior outcomes are based on ground truth. Consequently, the rate and degree to which an agent's expectations diverge from ground truth provide measures of that agent's SA/SU.

Middleton, Victor E.↗

NASA NTRS2012

Understanding Group/Party Affiliation Using Social Networks and Agent-Based Modeling

The dynamics of group affiliation and group dispersion is a concept that is most often studied in order for political candidates to better understand the most efficient way to conduct their campaigns. While political campaigning in the United States is a very hot topic that most politicians analyze and study, the concept of group/party affiliation presents its own area of study that producers very interesting results. One tool for examining party affiliation on a large scale is agent-based modeling (ABM), a paradigm in the modeling and simulation (M&S) field perfectly suited for aggregating individual behaviors to observe large swaths of a population. For this study agent based modeling was used in order to look at a community of agents and determine what factors can affect the group/party affiliation patterns that are present. In the agent-based model that was used for this experiment many factors were present but two main factors were used to determine the results. The results of this study show that it is possible to use agent-based modeling to explore group/party affiliation and construct a model that can mimic real world events. More importantly, the model in the study allows for the results found in a smaller community to be translated into larger experiments to determine if the results will remain present on a much larger scale.

Campbell, Kenyth↗

NASA NTRS2012

Exploring the Use of Computer Simulations in Unraveling Research and Development Governance Problems

Understanding Research and Development (R&D) enterprise relationships and processes at a governance level is not a simple task, but valuable decision-making insight and evaluation capabilities can be gained from their exploration through computer simulations. This paper discusses current Modeling and Simulation (M&S) methods, addressing their applicability to R&D enterprise governance. Specifically, the authors analyze advantages and disadvantages of the four methodologies used most often by M&S practitioners: System Dynamics (SO), Discrete Event Simulation (DES), Agent Based Modeling (ABM), and formal Analytic Methods (AM) for modeling systems at the governance level. Moreover, the paper describes nesting models using a multi-method approach. Guidance is provided to those seeking to employ modeling techniques in an R&D enterprise for the purposes of understanding enterprise governance. Further, an example is modeled and explored for potential insight. The paper concludes with recommendations regarding opportunities for concentration of future work in modeling and simulating R&D governance relationships and processes.

Balaban, Mariusz A.↗

NASA NTRS2012

Modern Warfare: An M and S Examination of the Dynamic Impact of Warlords and Insurgents on State Stability

9/11 changed the world as we knew it. Part of this change was to redirect the military of the United States away from focusing primarily on conventional conflict to a primary focus on unconventional or irregular conflict. This change required a tremendous learning effort by the military and their supporting research and development community. This learning effort included relearning of old but largely forgotten lessons as well as acquiring newly discovered knowledge. During the process of our immediate 9/11 response, we identified that we were engaged in Iraq and Afghanistan in an insurgency. Subsequently, our focus converged upon the description of insurgencies and the requirements for counterinsurgency. This paper argues that emerging conditions now allow the re-evaluation of the type of conflict occurring today and into the foreseeable future: that we, including the modeling and simulation world, emerge from a singular focus on orthodox insurgencies and start to consider the consequences and opportunities of the complexity of current conflicts. As an example of complexity, this paper will use the relatively common phenomenon of the Warlord or Warlordism. The paper will provide a definition of this phenomenon and then describe the implications for modelers. The paper will conclude by demonstrating the impact of incorporating this one rather prosaic complexity into an insurgency model, using agent based modeling (ABM).

Jones, Phillip N.↗

NASA NTRS2012

A Model of Rapid Radicalization Behavior Using Agent-Based Modeling and Quorum Sensing

Understanding the dynamics of radicalization, especially rapid radicalization, has become increasingly important to US policy in the past several years. Traditionally, radicalization is considered a slow process, but recent social and political events demonstrate that the process can occur quickly. Examining this rapid process, in real time, is impossible. However, recreating an event using modeling and simulation (M&S) allows researchers to study some of the complex dynamics associated with rapid radicalization. We propose to adapt the biological mechanism of quorum sensing as a tool to explore, or possibly explain, rapid radicalization. Due to the complex nature of quorum sensing, M&S allows us to examine events that we could not otherwise examine in real time. For this study, we employ Agent Based Modeling (ABM), an M&S paradigm suited to modeling group behavior. The result of this study was the successful creation of rapid radicalization using quorum sensing. The Battle of Mogadishu was the inspiration for this model and provided the testing conditions used to explore quorum sensing and the ideas behind rapid radicalization. The final product has wider applicability however, using quorum sensing as a possible tool for examining other catalytic rapid radicalization events.

Schwartz, Noah↗

NASA NTRS2013

Development of Autonomous Aerobraking - Phase 2

Phase 1 of the Development of Autonomous Aerobraking (AA) Assessment investigated the technical capability of transferring the processes of aerobraking maneuver (ABM) decision-making (currently performed on the ground by an extensive workforce and communicated to the spacecraft via the deep space network) to an efficient flight software algorithm onboard the spacecraft. This document describes Phase 2 of this study, which was a 12-month effort to improve and rigorously test the AA Development Software developed in Phase 1. Aerobraking maneuver; Autonomous Aerobraking; Autonomous Aerobraking Development Software; Deep Space Network; NASA Engineering and Safety Center

Murri, Daniel G.↗

DOE OSTI2021

Application of the DNAS framework expansion to occupant population synthesis

Research in occupant behaviour is now using a more elaborate framework of building occupant interaction. Researchers often face challenges in collecting data, particularly for the data to meet the minimum number of required data points and the data interoperability requirements. Researchers address the first issue with the synthetic population and the latter with data ontologies. While synthetic population is commonly used to address the first issue, data ontology development is used to address the latter. The two solutions are complementary to each other. One of the known ontologies in building occupant behaviour research is the Drivers-Needs-Actions-Systems (DNAS) ontology, which has been used by building modelers to describe energy-related occupant behaviour. This paper describes the ontology-based synthetic population generation that can be used in the agent-based modeling (ABM) applications. This paper considers multiple data sources, including ASHRAE Thermal Comfort DB II and IEA Annex 66 data sets. A case study of an office building is used to present the workflow of DNAS framework expansion, synthetic population generation, and agent-based modeling.

Chandra Putra, Handi↗

DOE OSTI2022

Multi-Level Impacts of Extreme Climate-Related Events on Food Supply Chain: Idaho Potato's Case Study

Background: The world is experiencing frequent extreme weather events like droughts, floods, snowstorms, and shifting of seasons due to climate change. Increasing frequencies and severity of these extreme weather events threaten food security because agriculture is extremely vulnerable to climate change. Higher temperature reduces overall yields of the desirable crops but proliferates weeds and harmful pests. Current data shows that every year U.S. farmers spend more than 11 billion USD to fight weeds and this number is expected to rise in the coming years due to climate change. Due to droughts, the water required for irrigation is becoming scarcer. Since many areas are becoming climatically unusable for crop production, the amount of farmland area is shrinking rapidly. In addition, changes in precipitation patterns are causing crop failures and negatively impacting expected yields. In this study, we investigated how different extreme climate events impact different stages of a food supply chain. Approach: As a case study, we chose Idaho’s potato supply chain (SC). Idaho is the top potato producing state in the U.S. and contributes around 30% of the nation’s potato production. Using the agent-based modeling (ABM) approach, we developed a multi-echelon potato supply chain computer simulation model with six types of agents – seed producers, farmers, shippers, processors, retailers, and logistics companies. In addition to the baseline scenario, we developed two additional climate-related disruption events – drought and snowstorm. We investigated how each of these disruption events impacts different stakeholders across the supply chain in terms of revenue and some other key performance metrics such as lead time, food waste, number of delayed orders, and order fulfillment rate. Results: Extreme climate events not only impact the growers but there is also cascading ripple effects downstream of the supply chain. The methodology developed in this study could be applied to other food and agricultural SC to understand the vulnerabilities of the different links. The findings would potentially help to adopt new policies for the well-being of the overall SC.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Analyzing the co-evolution of green technology diffusion and consumers’ pro-environmental attitudes: An agent-based model

Massive diffusion of green technologies is significant for building a cleaner world. However, the process of technology diffusion is usually slow and complex. An in-depth understanding of the mechanism regarding green technology diffusion is an essential precondition for effectively stimulating this process. Green technology diffusion heavily involves both social and technological changes. Although existing studies have provided rich knowledge about identifying critical drivers and barriers affecting green technology diffusion, research that considers consumers’ pro-environmental attitudes and green technology diffusion as an evolving system is still sparse. Aiming at exploring the co-evolution of consumers’ pro-environmental attitudes and green technology diffusion, this paper builds an agent-based model that integrates the relative agreement model with technology diffusion theories to conduct a sequence of controlled numerical experiments, which progressively unveil how attitudinal and technological factors impact green technology diffusion. The main findings include that (1) improving consumers’ pro-environmental attitudes is prominently beneficial to green technology diffusion and maturation; (2) technology maturity has very limited impact on consumers’ first-time purchases but significantly affects consumers’ satisfaction, which would further impact consumers’ repeat purchases; (3) consumers that do not support green technologies frequently emerge during the evolution of attitudes (despite the high technology maturity), which corresponds to the emergence of the anti-environmental groups observed in the real world; (4) active interactions between non-adopters enable their attitudes to converge, which results in the polarization of consumers’ attitudes.

ABM↗

NASA NTRSDate not supplied

Auxetic Thermo-Responsive Shape-Memory Polyurethane Aerogels

Shape memory polymer aerogels are stimuli-responsive aerogel materials that incorporate polymer aerogel characteristics such as flexibility at low density, and high porosity with shape-changing capabilities upon exposure to external stimuli. By designing the structure of these materials at meso- to macroscale, their shape memory response can be efficiently engineered to show an auxetic response such as a negative Poisson’s ratio, leading to an active and tunable metamaterial. We present a material technology based on a shape memory polyurethane aerogel derived from aliphatic triisocyanate and triethylene glycol, which demonstrates and remembers an auxetic shape change through a thermomechanical cycle first below, and then back again above the glass transition temperature of the polyurethane. Our auxetic shape memory polyurethane aerogels exhibit a significant auxetic response with a negative Poisson’s ratio of approximately -0.8 at 15% compressive strain. This technology is expected to impact multiple areas of interest in relation to commercial, aeronautic, and aerospace industries. Potential applications include minimally invasive medical technologies, soft robotics, and self-deployable structures and habitats. Structure-property relationships of the auxetic shape memory polymer aerogels will be discussed.

Sadeq Malakooti↗

NASA NTRS2021

Meta-aerogels: Auxetic Shape-memory Polyurethane Aerogels

Shape-memory poly(isocyanurate-urethane) (PIR-PUR) aerogels are low-density monolithic nanoporous solids that remember and return to their permanent shape through a heating actuation step. Herein, through structural design at the macro scale, the shape-memory response is augmented with an auxetic effect manifested by a negative Poisson’s ratio of approximately -0.8 at 15% compressive strain. Thus, auxetic shape-memory PIR-PUR monoliths experience volume contraction upon compression at a temperature above the glass transition temperature of the base polymer (Tg ~ 30 °C), and they can be stowed indefinitely in that temporary shape by cooling below Tg. By heating back above Tg, the compressed/shrunk form expands back to their original shape/size. This technology is relevant to a broad range of industries spanning the commercial, aeronautical, and aerospace sectors. The materials are referred to as meta-aerogels and their potential applications include minimally invasive medical devices, soft robotics, and in situations where volume is at a premium, as for example for storage of deployable space structures and planetary habitats during transport to the point of service.

Sadeq Malakooti↗