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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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At least 19 records

Using Dynamic Simulations and Automated Decision Tools to Design Lunar Habitats

This paper describes the role of transient simulations, heuristic techniques, and closed loop integrated control in designing and sizing habitat life support systems. The integration of these three elements allows for more accurate requirements to be derived in advance of hardware choices. As a test case, we used a typical lunar surface habitat. Large numbers of habitat configurations were rapidly tested and evaluated using automated decision support tools. Through this process, preliminary sizing for habitat life support systems were derived. Our preliminary results show that by using transient simulations and closed loop control , we substantially reduced the system mass required to meet mission goals. This has greater implications for general systems analyses and for life support systems. It is likely that transient models, realtime integrated control, and other analyses capable of capturing the uncertainties of systems can be useful for systems analyses much earlier in the system development life cycle than has previously been considered.

Bell, Scott↗

Agrivoltaic Decision Tools for Perennial and Field Crop Farmers

This article describes a series of spreadsheet-based tools to help farmers estimate costs, revenues, and yields from agricultural production under different configurations of agrivoltaic installations for field and perennial crops. Crop-specific log books allow farmers to project changes in activity-level costs from the field due to agrivoltaic installations. The whole-farm tool helps farmers aggregate activity-level net returns up to the farm level to calculate projections of trade-offs between crop production with or without agrivoltaic installations. We present tools for lettuce and cranberries, but the tools are comprehensive and inclusive and so can be modified for other perennial and field crops.

14 SOLAR ENERGY↗

Development of an Optimal Water Allocation Decision Tool for the Major Crops During the Water Deficit Period in the Southeast U.S.

We developed a dynamic model to optimize irrigation application in three major crops (corn, cotton and peanuts) grown in the Southeast USA. Water supply amount is generated from an engineering model which is then combined with economic models to find the optimal amount of irrigation water to apply on each crop field during the six critical water deficit weeks in summer. Results indicate that water is applied on the crop with the highest marginal value product of irrigation. Decision making tool such as the one developed here would help farmers and policy makers to find the maximum profitable solution when water shortage is a serious concern.

Paudel, Krishna P.↗

Partner with a Third-Party Delivery Service or Not? A Prediction-and-Decision Tool for Restaurants Facing Takeout Demand Surges During a Pandemic

Amidst the COVID-19 pandemic, restaurants become more reliant on no-contact pick-up or delivery ways for serving customers. As a result, they need to make tactical planning decisions such as whether to partner with online platforms, to form their own delivery team, or both. In this paper, we develop an integrated prediction-decision model to analyze the profit of combining the two approaches and to decide the needed number of drivers under stochastic demand. We first use the susceptible-infected-recovered (SIR) model to forecast future infected cases in a given region and then construct an autoregressive-moving-average (ARMA) regression model to predict food-ordering demand. Using predicted demand samples, we formulate a stochastic integer program to optimize food delivery plans. We conduct numerical studies using COVID-19 data and food-ordering demand data collected from local restaurants in Nuevo Leon, Mexico, from April to October 2020, to show results for helping restaurants build contingency plans under rapid market changes. Our method can be used under unexpected demand surges, various infection/vaccination status, and demand patterns. Here, our results show that a restaurant can benefit from partnering with third-party delivery platforms when (i) the subscription fee is low, (ii) customers can flexibly decide whether to order from platforms or from restaurants directly, (iii) customers require more efficient delivery, (iv) average delivery distance is long, or (v) demand variance is high.

97 MATHEMATICS AND COMPUTING↗

Risk based decision tool for space exploration missions

This paper presents an approach and corresponding tool to assess and analyze the risks involved in a mission during the pre-phase A design process. This approach is based on creating a risk template for each subsystem expert involved in the mission design process and defining appropriate interactions between the templates.

space exploration proposals↗

A Decision Tool that Combines Discrete Event Software Process Models with System Dynamics Pieces for Software Development Cost Estimation and Analysis

The development process for a large software development project is very complex and dependent on many variables that are dynamic and interrelated. Factors such as size, productivity and defect injection rates will have substantial impact on the project in terms of cost and schedule. These factors can be affected by the intricacies of the process itself as well as human behavior because the process is very labor intensive. The complex nature of the development process can be investigated with software development process models that utilize discrete event simulation to analyze the effects of process changes. The organizational environment and its effects on the workforce can be analyzed with system dynamics that utilizes continuous simulation. Each has unique strengths and the benefits of both types can be exploited by combining a system dynamics model and a discrete event process model. This paper will demonstrate how the two types of models can be combined to investigate the impacts of human resource interactions on productivity and ultimately on cost and schedule.

Mizell, Carolyn Barrett↗

Hydropower Potential at Non-Powered Dams: A Multi-Criteria Decision Analysis Tool based on Grid, Community, Industry, and Environmental Impacts

Non-powered dams (NPDs) are dams that do not include hydraulic turbine (hydropower) equipment. Currently, there are more than 80,000 such dams in the United States, which provide a variety of non-energy benefits, including flood control, water supply, navigation, and recreation. Approximately 500 of these NPDs are identified as having the potential to add hydropower generation (totaling up to a capacity of more than 8200 MW). A large share of investment costs and environmental impacts of dam construction have already been incurred at these NPDs. Hence, adding power to the existing dam structure is hypothesized to be achieved at a lower cost, with less risk, and a shorter timeframe than the development required for new dam construction. The abundance of NPDs, the associated environmental favorability, and cost advantages, combined with the reliability, predictability, and dispatchability of hydropower, make NPDs a strong candidate in the nation’s renewable energy portfolio. To assess the NPD to hydropower conversion potential, in this study, we developed a GIS-based multi-criterial decision analysis tool, which allows users to rank these NPDs based on the grid, community, industry, and environmental impacts (i.e., GCIE impacts). This web-based interactive tool (developed using open-source Python and JavaScript) lets the user choose from a wide range of features to define each of the GCIE impact scores through a user-friendly graphical user interface. These features are related to dam operation, hydropower generation opportunity, power market economy, social vulnerability and risk, proximity to critical infrastructure and energy generating facilities, environmental concerns (air, water, and critical habitat), and exposure to natural hazards. The overall priority score of NPDs is calculated based on user-defined weights for each of the GCIE impact scores. Besides ranking NPDs, the tool can also be used to estimate the energy-storage feasibility (battery, hydrogen, and pump-storage hydropower) at each of the potential sites.

13 HYDRO ENERGY↗

Decision blocks: A tool for automating decision making in CLIPS

The human capability of making complex decision is one of the most fascinating facets of human intelligence, especially if vague, judgemental, default or uncertain knowledge is involved. Unfortunately, most existing rule based forward chaining languages are not very suitable to simulate this aspect of human intelligence, because of their lack of support for approximate reasoning techniques needed for this task, and due to the lack of specific constructs to facilitate the coding of frequently reoccurring decision block to provide better support for the design and implementation of rule based decision support systems. A language called BIRBAL, which is defined on the top of CLIPS, for the specification of decision blocks, is introduced. Empirical experiments involving the comparison of the length of CLIPS program with the corresponding BIRBAL program for three different applications are surveyed. The results of these experiments suggest that for decision making intensive applications, a CLIPS program tends to be about three times longer than the corresponding BIRBAL program.

Eick, Christoph F.↗

Small Hydropower Interconnection: Decision Support Tool User Guide

The Small Hydropower Interconnection Decision Support Tool is designed to provide specific information to small hydropower developers about the interconnection process. Developers follow this user guide to understand the general process; the Small Hydropower Interconnection Tool accompanies this user guide and provides specific knowledge of the processes and costs pertinent to specific locations.

13 HYDRO ENERGY↗

Decision Support Tool for Solar Energy Cybersecurity Policy and Regulation

The Decision Support Tool helps users address four discrete challenges: (1) complex requirements of relevant codes and standards, (2) technical complexity of solar assets, (3) undefined cyber risk severity, and (4) unclear roles and responsibilities. Content includes an analysis of cyber vulnerability risks, a decision support resource for policymakers to mitigate cyber risks to solar photovoltaic systems, and background resources for informing policy development. A key component of this tool is the Probable Risk Assessment (PRA), based on established, formal variables, models, and consequences, which helps users understand the determined risk and assigned ownership of the physical components. It helps states draw logical lines between vulnerabilities and mitigative solutions, of which some have been further detailed as Cybersecurity Advisory Team for State Solar (CATSS) tools.

14 SOLAR ENERGY↗

The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Space Flight Medical Systems

The Integrated Medical Model (IMM) is a decision support tool that is useful to mission planners and medical system designers in assessing risks and designing medical systems for space flight missions. The IMM provides an evidence based approach for optimizing medical resources and minimizing risks within space flight operational constraints. The mathematical relationships among mission and crew profiles, medical condition incidence data, in-flight medical resources, potential crew functional impairments, and clinical end-states are established to determine probable mission outcomes. Stochastic computational methods are used to forecast probability distributions of crew health and medical resource utilization, as well as estimates of medical evacuation and loss of crew life. The IMM has been used in support of the International Space Station (ISS) medical kit redesign, the medical component of the ISS Probabilistic Risk Assessment, and the development of the Constellation Medical Conditions List. The IMM also will be used to refine medical requirements for the Constellation program. The IMM outputs for ISS and Constellation design reference missions will be presented to demonstrate the potential of the IMM in assessing risks, planning missions, and designing medical systems. The implementation of the IMM verification and validation plan will be reviewed. Additional planned capabilities of the IMM, including optimization techniques and the inclusion of a mission timeline, will be discussed. Given the space flight constraints of mass, volume, and crew medical training, the IMM is a valuable risk assessment and decision support tool for medical system design and mission planning.

Kerstman, Eric↗

Assessing the Hydrologic Performance of the EPA's Nonpoint Source Water Quality Assessment Decision Support Tool Using North American Land Data Assimilation System (Products)

The accuracy of streamflow predictions in the EPA's BASINS (Better Assessment Science Integrating Point and Nonpoint Sources) decision support tool is affected by the sparse meteorological data contained in BASINS. The North American Land Data Assimilation System (NLDAS) data with high spatial and temporal resolutions provide an alternative to the NOAA National Climatic Data Center (NCDC)'s station data. This study assessed the improvement of streamflow prediction of the Hydrological Simulation Program-FORTRAN (HSPF) model contained within BASINS using the NLDAS 118 degree hourly precipitation and evapotranspiration estimates in seven watersheds of the Chesapeake Bay region. Our results demonstrated consistent improvements of daily streamflow predictions in five of the seven watersheds when NLDAS precipitation and evapotranspiration data was incorporated into BASINS. The improvement of using the NLDAS data is significant when watershed's meteorological station is either far away or not in a similar climatic region. When the station is nearby, using the NLDAS data produces similar results. The correlation coefficients of the analyses using the NLDAS data were greater than 0.8, the Nash-Sutcliffe (NS) model fit efficiency greater than 0.6, and the error in the water balance was less than 5%. Our analyses also showed that the streamflow improvements were mainly contributed by the NLDAS's precipitation data and that the improvement from using NLDAS's evapotranspiration data was not significant; partially due to the constraints of current BASINS-HSPF settings. However, NLDAS's evapotranspiration data did improve the baseflow prediction. This study demonstrates the NLDAS data has the potential to improve stream flow predictions, thus aid the water quality assessment in the EPA nonpoint water quality assessment decision tool.

Lee, S.↗

Wind Prediction Accuracy for Air Traffic Management Decision Support Tools

The performance of Air Traffic Management and flight deck decision support tools depends in large part on the accuracy of the supporting 4D trajectory predictions. This is particularly relevant to conflict prediction and active advisories for the resolution of conflicts and the conformance with of traffic-flow management flow-rate constraints (e.g., arrival metering / required time of arrival). Flight test results have indicated that wind prediction errors may represent the largest source of trajectory prediction error. The tests also discovered relatively large errors (e.g., greater than 20 knots), existing in pockets of space and time critical to ATM DST performance (one or more sectors, greater than 20 minutes), are inadequately represented by the classic RMS aggregate prediction-accuracy studies of the past. To facilitate the identification and reduction of DST-critical wind-prediction errors, NASA has lead a collaborative research and development activity with MIT Lincoln Laboratories and the Forecast Systems Lab of the National Oceanographic and Atmospheric Administration (NOAA). This activity, begun in 1996, has focussed on the development of key metrics for ATM DST performance, assessment of wind-prediction skill for state of the art systems, and development/validation of system enhancements to improve skill. A 13 month study was conducted for the Denver Center airspace in 1997. Two complementary wind-prediction systems were analyzed and compared to the forecast performance of the then standard 60 km Rapid Update Cycle - version 1 (RUC-1). One system, developed by NOAA, was the prototype 40-km RUC-2 that became operational at NCEP in 1999. RUC-2 introduced a faster cycle (1 hr vs. 3 hr) and improved mesoscale physics. The second system, Augmented Winds (AW), is a prototype en route wind application developed by MITLL based on the Integrated Terminal Wind System (ITWS). AW is run at a local facility (Center) level, and updates RUC predictions based on an optimal interpolation of the latest ACARS reports since the RUC run. This paper presents an overview of the study's results including the identification and use of new large mor wind-prediction accuracy metrics that are key to ATM DST performance.

Cole, Rod↗

A Flight Deck Decision Support Tool for Autonomous Airborne Operations

NASA is developing a flight deck decision support tool to support research into autonomous operations in a future distributed air/ground traffic management environment. This interactive real-time decision aid, referred to as the Autonomous Operations Planner (AOP), will enable the flight crew to plan autonomously in the presence of dense traffic and complex flight management constraints. In assisting the flight crew, the AOP accounts for traffic flow management and airspace constraints, schedule requirements, weather hazards, aircraft operational limits, and crew or airline flight-planning goals. This paper describes the AOP and presents an overview of functional and implementation design considerations required for its development. Required AOP functionality is described, its application in autonomous operations research is discussed, and a prototype software architecture for the AOP is presented.

Ballin, Mark G.↗

Autonomous Task Management and Decision Support Tools

For some time aircraft manufacturers and researchers have been pursuing mechanisms for reducing crew workload and providing better decision support to the pilots, especially during non-normal situations. Some previous attempts to develop task managers or pilot decision support tools have not resulted in robust and fully functional systems. However, the increasing sophistication of sensors and automated reasoners, and the exponential surge in the amount of digital data that is now available create a ripe environment for the development of a robust, dynamic, task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This presentation will discuss the many significant challenges and issues associated with the development and functionality of such a system for use on the aircraft flight deck.

decision support↗

A Life-Cycle Cost Estimating Methodology for NASA-Developed Air Traffic Control Decision Support Tools

This paper describes the development of a life-cycle cost (LCC) estimating methodology for air traffic control Decision Support Tools (DSTs) under development by the National Aeronautics and Space Administration (NASA), using a combination of parametric, analogy, and expert opinion methods. There is no one standard methodology and technique that is used by NASA or by the Federal Aviation Administration (FAA) for LCC estimation of prospective Decision Support Tools. Some of the frequently used methodologies include bottom-up, analogy, top-down, parametric, expert judgement, and Parkinson's Law. The developed LCC estimating methodology can be visualized as a three-dimensional matrix where the three axes represent coverage, estimation, and timing. This paper focuses on the three characteristics of this methodology that correspond to the three axes.

Wang, Jianzhong Jay↗