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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Systematic Approach to Developing Sustainable Post-Disaster Shelters in the Southern Region of the United States

This study aims to propose a sustainable shelter design involving energy savings, less environmental impact, and rapid construction. The structural design of the shelter is based on 3D-printing technology. Sustainability assessments, including life cycle analysis (LCA), life cycle energy assessment (LCEA), and energy justice of the designed shelter, were conducted to prove the sustainable shelter design. The outcomes of this study for several scenarios will not only allow decision-makers to design permanent shelters with maximized utilization of limited resources but also help local communities strengthen their ability to recover with minimal outside assistance post-disaster. Furthermore, residents can utilize the sustainable shelter to maintain critical functions, including business continuity and local business in emergencies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Integrated Design Results for the MSR SRC Mars Ascent Vehicle

The primary mission of the NASA Mars Sample Return (MSR) Campaign is to return samples of the Martian surface to Earth for scientific study. As part of this campaign, NASA is developing a Mars Ascent Vehicle (MAV). This vehicle must survive an approximate two year journey to the Martian surface as a payload aboard a separate lander spacecraft. After residing on the surface for another year, the MAV will carry a payload of samples into orbit. From there, following ejection from the MAV, the samples will rendezvous with an Earth return spacecraft for capture, and ultimately, return to Earth.The design of the MAV represents a number of unique challenges, as no launch vehicle has ever left the surface of a planet other than Earth. Although conceptual designs for a MAV have been in various levels of development since the 1970s, none have achieved the level of fidelity and support that exists in the current MSR-MAV design. Early MSR-MAV concept studies examined multiple methods of propulsion, ultimately deciding that a Two Stage to Orbit (TSTO) solid propulsion vehicle would provide the most capable performance in a Martian environment. Following this key architecture decision, the vehicle design was further matured to a Solid-Solid Guided-Guided (SSGG) architecture for NASA Key Decision Point A (KDP-A). Although the SSGG design was able to meet all mission constraints, concerns were raised regarding limited mass margin on other elements of the MSR campaign at such an early phase. A design challenge was issued to reduce MAV total mass by as much as possible. It was ultimately determined that by moving a number of components of the vehicle second stage to the first stage, the overall vehicle mass could be reduced significantly. The new design featured a much smaller and completely unguided second stage. This paper describes the resultant Solid-Solid Guided-Unguided (SSGU) MAV design concept developed as part of the Systems Requirement Cycle (SRC). This design was developed primarily by NASA Marshall Space Flight Center (MSFC), in association with NASA Jet Propulsion Laboratory (JPL) and NASA Langley Research Center (LaRC). The TSTO vehicle includes one solid rocket motor per stage. As the vehicle second stage is unguided, it features spin-stabilization to maintain vehicle stability during flight. An electromechanically actuated Thrust Vector Control (TVC) and a monopropellant Reaction Control System (RCS) is employed for active guidance on the first stage. The vehicle is designed to deliver up to 0.47kg of Martian samples to a Mars circular orbit of 380km at 27° inclination. Due to the extremely unique design constraints of this mission, and a recent transition to a Risk Class A posture, the MAV team was compelled to devise unconventional solutions to the vehicle design. The detailed design and analysis of these subsystems and the vehicle as a whole are discussed in this paper relative to all of the engineering disciplines involved.

MSR↗
NASA NTRSDate not supplied

Integrated Design Results for the MSR SRC Mars Ascent Vehicle

The primary mission of the NASA Mars Sample Return (MSR) Campaign is to return samples of the Martian surface to Earth for scientific study. As part of this campaign, NASA is developing a Mars Ascent Vehicle (MAV). This vehicle must survive an approximate two-year journey to the Martian surface as a payload aboard a separate lander spacecraft. After residing on the surface for another year, the MAV will carry a payload of samples into orbit. From there, following ejection from the MAV, the samples will rendezvous with an Earth return spacecraft for capture, and ultimately, return to Earth. The design of the MAV represents a number of unique challenges, as no launch vehicle has ever left the surface of a planet other than Earth. Although conceptual designs for a MAV have been in various levels of development since the 1970s, none have achieved the level of fidelity and support that exists in the current MSR-MAV design. Early MSR-MAV concept studies examined multiple methods of propulsion, ultimately deciding that a Two-Stage-to-Orbit (TSTO) solid propulsion vehicle would provide the most capable performance in a Martian environment. Following this key architecture decision, the vehicle design was further matured to a Solid-Solid Guided-Guided (SSGG) architecture for NASA Key Decision Point A (KDP-A). Although the SSGG design was able to meet all mission constraints, concerns were raised regarding limited mass margin on other elements of the MSR campaign at such an early phase. A design challenge was issued to reduce MAV total mass by as much as possible. It was ultimately determined that by moving a number of components of the vehicle second stage to the first stage, the overall vehicle mass could be reduced significantly. The new design features a much smaller and completely unguided second stage. This paper describes the resultant Solid-Solid Guided-Unguided (SSGU) MAV design concept developed as part of the Systems Requirement Cycle (SRC). This design was developed primarily by NASA Marshall Space Flight Center (MSFC), in association with NASA Jet Propulsion Laboratory (JPL) and NASA Langley Research Center (LaRC). The TSTO vehicle includes one solid rocket motor per stage. As the vehicle second stage is unguided, it features spin-stabilization to maintain vehicle stability during flight. An electromechanically actuated Thrust Vector Control (TVC) system and a monopropellant Reaction Control System (RCS) are employed for active guidance on the first stage. The vehicle is designed to deliver up to 0.47kg of Martian samples to a Mars circular orbit of 380km at 27° inclination. Due to the extremely unique design constraints of this mission, and a recent transition to a Risk Class A posture, the MAV team was compelled to devise unconventional solutions to the vehicle design. The detailed design and analysis of these subsystems and the vehicle as a whole are discussed in this paper relative to all of the engineering disciplines involved.

MAV↗
NASA NTRS2006

Architecting Space Exploration Campaigns: A Decision-Analytic Approach

This paper shows the benefits of Decision Analysis techniques for campaign design and evaluation. Important concepts of decision analysis are reviewed through the lens of designing a campaign to find exploitable equatorial water on Mars. The method developed herein is general to any search campaign. The paper concludes with a discussion of the challenges and opportunities in applying similar techniques to other types of campaigns.

campaigns↗
NASA NTRS1987

Compromise - An effective approach for the hierarchical design of structural systems

The use of the compromise decision support problem in hierarchical design of structural systems is described. The mathematical template that supports the underlying precepts of hierarchical design in the context of the decision support problem technique is presented. A structural example that demonstrates the efficacy of the approach is included.

Shupe, J. A.↗
NASA NTRS1995

DREAMS and IMAGE: A Model and Computer Implementation for Concurrent, Life-Cycle Design of Complex Systems

Computing architectures are being assembled that extend concurrent engineering practices by providing more efficient execution and collaboration on distributed, heterogeneous computing networks. Built on the successes of initial architectures, requirements for a next-generation design computing infrastructure can be developed. These requirements concentrate on those needed by a designer in decision-making processes from product conception to recycling and can be categorized in two areas: design process and design information management. A designer both designs and executes design processes throughout design time to achieve better product and process capabilities while expanding fewer resources. In order to accomplish this, information, or more appropriately design knowledge, needs to be adequately managed during product and process decomposition as well as recomposition. A foundation has been laid that captures these requirements in a design architecture called DREAMS (Developing Robust Engineering Analysis Models and Specifications). In addition, a computing infrastructure, called IMAGE (Intelligent Multidisciplinary Aircraft Generation Environment), is being developed that satisfies design requirements defined in DREAMS and incorporates enabling computational technologies.

Hale, Mark A.↗
NASA NTRS1994

Integration of the Response Surface Methodology with the Compromise Decision Support Problem in Developing a General Robust Design Procedure

In this paper we introduce a comprehensive and rigorous robust design procedure to overcome some limitations of the current approaches. A comprehensive approach is general enough to model the two major types of robust design applications, namely, robust design associated with the minimization of the deviation of performance caused by the deviation of noise factors (uncontrollable parameters), and robust design due to the minimization of the deviation of performance caused by the deviation of control factors (design variables). We achieve mathematical rigor by using, as a foundation, principles from the design of experiments and optimization. Specifically, we integrate the Response Surface Method (RSM) with the compromise Decision Support Problem (DSP). Our approach is especially useful for design problems where there are no closed-form solutions and system performance is computationally expensive to evaluate. The design of a solar powered irrigation system is used as an example. Our focus in this paper is on illustrating our approach rather than on the results per se.

Chen, Wei↗
NASA NTRS2017

Automation of POST Cases via External Optimizer and "Artificial p2" Calculation

During early conceptual design of complex systems, speed and accuracy are often at odds with one another. While many characteristics of the design are fluctuating rapidly during this phase there is nonetheless a need to acquire accurate data from which to down-select designs as these decisions will have a large impact upon program life-cycle cost. Therefore enabling the conceptual designer to produce accurate data in a timely manner is tantamount to program viability. For conceptual design of launch vehicles, trajectory analysis and optimization is a large hurdle. Tools such as the industry standard Program to Optimize Simulated Trajectories (POST) have traditionally required an expert in the loop for setting up inputs, running the program, and analyzing the output. The solution space for trajectory analysis is in general non-linear and multi-modal requiring an experienced analyst to weed out sub-optimal designs in pursuit of the global optimum. While an experienced analyst presented with a vehicle similar to one which they have already worked on can likely produce optimal performance figures in a timely manner, as soon as the "experienced" or "similar" adjectives are invalid the process can become lengthy. In addition, an experienced analyst working on a similar vehicle may go into the analysis with preconceived ideas about what the vehicle's trajectory should look like which can result in sub-optimal performance being recorded. Thus, in any case but the ideal either time or accuracy can be sacrificed. In the authors' previous work a tool called multiPOST was created which captures the heuristics of a human analyst over the process of executing trajectory analysis with POST. However without the instincts of a human in the loop, this method relied upon Monte Carlo simulation to find successful trajectories. Overall the method has mixed results, and in the context of optimizing multiple vehicles it is inefficient in comparison to the method presented POST's internal optimizer functions like any other gradient-based optimizer. It has a specified variable to optimize whose value is represented as optval, a set of dependent constraints to meet with associated forms and tolerances whose value is represented as p2, and a set of independent variables known as the u-vector to modify in pursuit of optimality. Each of these quantities are calculated or manipulated at a certain phase within the trajectory. The optimizer is further constrained by the requirement that the input u-vector must result in a trajectory which proceeds through each of the prescribed events in the input file. For example, if the input u-vector causes the vehicle to crash before it can achieve the orbital parameters required for a parking orbit, then the run will fail without engaging the optimizer, and a p2 value of exactly zero is returned. This poses a problem, as this "non-connecting" region of the u-vector space is far larger than the "connecting" region which returns a non-zero value of p2 and can be worked on by the internal optimizer. Finding this connecting region and more specifically the global optimum within this region has traditionally required the use of an expert analyst.

Dees, Patrick D.↗
DOE OSTI2025

First-of-a-Kind Risk-Informed Digital Twin for Operational Decision Making

A digital twin (DT) is a digital model or a collection of models of a physical entity. DTs in the nuclear arena can be used from plant design through decommissioning. Decisions are typically a priori or made offline. Risk-informed decision making is identifying what can go wrong, its frequency, and the consequences of its failure. Ideally risk-informed decision making reflects the current state of the plant and provides a decision in real time. Traditionally, probabilistic risk assessments (PRAs) evaluate the failures of safety systems, the risk of core damage, and the offsite dose as the consequence. However, this DT evaluates the decisions on the control side rather than the protection side. It uses the same risk methods to probabilistically inform the decision-making process but in a different way. Rather than evaluating the risk of core damage, this DT evaluates the likelihood of avoiding a trip set point while maintaining plant safety. Performance-based assessments are identified via its probabilistic evaluation of operational alternatives based on system status. Because the purpose of the control system is to maintain system variables within prescribed operating ranges, upsets or challenges that can exceed a trip set point resulting in a plant transient and a challenge to plant mitigating systems based on actual plant conditions, are evaluated to safely maintain the plant within the operating ranges. The probabilistic portion of the model is autonomously and automatically adjusted, and the metric of interest (i.e. likelihood of avoiding a trip set point) is recalculated. The digital representation of the physical system (i.e. the DT) performs a deterministic performance–based assessment of the probabilistically identified alternatives identified to validate the probabilistic assessment. A decision-making algorithm selects the appropriate option based on the probabilistic and deterministic assessments and transmits a control signal to a component(s) to initiate a corrective action or informs an operator of its decision.

digital twin↗
NASA NTRS2019

SAFE50 Reference Design Study for Large-Scale High-Density Low-Altitude UAS Operations in Urban Areas

Enabling safe, routine, and high-density flight operations of small UAS at low-altitude over heavily populated urban centers presents a difficult challenge for emerging UAS Traffic Management (UTM) system concepts. Urban operations by definition involve flight over people, property, and infrastructure. Low-altitude urban environments - such as urban canyons – are one of the most difficult areas for UTM to consider. Mission concepts require routine operations in a cluttered radio-frequency (RF) environment with degraded or denied Global Positioning System (GPS) reception. Flights with any appreciable distance will be beyond visual and communications line-of-sight from ground operators. Timely detection and response to emergencies and onboard failures, which is critical for safe aircraft operation, will be difficult. This work seeks to establish a feasible reference autonomy architecture for autonomous vehicles in an urban UTM system, then verifying and validating this architecture within a complete UTM concept point-design and systems analysis study. In this paper, we present the results from the NASA SAFE50 conceptual design and systems study that investigates the trade-space of urban UTM operations. This advanced conceptual design study develops a feasible, verified, validated point-design solution. The SAFE50 point-design concept places emphasis on advanced, highly-autonomous, and highly-capable vehicles that favors intelligent onboard autonomy over direct human control with today's technologies and operating in today's urban environments. This paper focuses on an general overview of the design study, highlighting decisions made in the architectural solution. This paper will presents a summary of the study, architectures, and requirements. We present an overview of the architecture designs as derived from the top-level UTM system. The point-design has been implemented in both simulation and through flight testing of hardware design prototypes. The results from simulation and flight testing as part of the verification and validation process of the reference design study.

Ippolito, Corey A.↗
NASA NTRS1988

Multiple degree of freedom object recognition using optical relational graph decision nets

Multiple-degree-of-freedom object recognition concerns objects with no stable rest position with all scale, rotation, and aspect distortions possible. It is assumed that the objects are in a fairly benign background, so that feature extractors are usable. In-plane distortion invariance is provided by use of a polar-log coordinate transform feature space, and out-of-plane distortion invariance is provided by linear discriminant function design. Relational graph decision nets are considered for multiple-degree-of-freedom pattern recognition. The design of Fisher (1936) linear discriminant functions and synthetic discriminant function for use at the nodes of binary and multidecision nets is discussed. Case studies are detailed for two-class and multiclass problems. Simulation results demonstrate the robustness of the processors to quantization of the filter coefficients and to noise.

Casasent, David P.↗
NASA NTRS2011

Backplane Design Considerations for High Speed SpaceWire Networks

SpaceWire is becoming a preferred protocol for board to board communication over a backplane in addition to its existing use over cabled interfaces, replacing other protocols due to its simplicity and readily available flight quality physical layer devices, IP cores and test equipment. However, without specific guidelines for implementing SpaceWire over a backplane, designers are left to make trade decisions regarding connector selection, layout design rules and test accessibility issues. This paper will discuss NASA's Goddard Space Flight Center s implementation of high speed SpaceWire over backplane on James Webb Space Telescope and other missions.

Pagen, Shahana Aziz↗
NASA NTRS2004

Reducing Design Cycle Time and Cost Through Process Resequencing

In today's competitive environment, companies are under enormous pressure to reduce the time and cost of their design cycle. One method for reducing both time and cost is to develop an understanding of the flow of the design processes and the effects of the iterative subcycles that are found in complex design projects. Once these aspects are understood, the design manager can make decisions that take advantage of decomposition, concurrent engineering, and parallel processing techniques to reduce the total time and the total cost of the design cycle. One software tool that can aid in this decision-making process is the Design Manager's Aid for Intelligent Decomposition (DeMAID). The DeMAID software minimizes the feedback couplings that create iterative subcycles, groups processes into iterative subcycles, and decomposes the subcycles into a hierarchical structure. The real benefits of producing the best design in the least time and at a minimum cost are obtained from sequencing the processes in the subcycles.

Rogers, James L.↗
DOE OSTI2025

A matheuristic for design and dispatch of a utility-connected distributed energy system

Modeling distributed power generation systems often requires complicated mathematical expressions that present challenges for commercial optimization solvers. Here, this paper presents a matheuristic to solve a mixed-integer optimization model that informs decisions regarding the design and dispatch of a utility-connected microgrid. We deploy a genetic algorithm to search the system design space and a linear program to solve the economic dispatch problem. The model is a component of a web tool that requires solutions within a few minutes. Our method yields objective function values within 5% of an exogenously produced optimal in fewer than 30 seconds for 90% of our test cases compared to only 10% of our test cases by a traditional optimization solver in the same amount of time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Microgrid design and multi-year dispatch optimization under climate-informed load and renewable resource uncertainty

Microgrids are an increasingly popular solution to provide energy resilience in response to increasing grid dependency and the growing impacts of climate change on grid operations. However, existing microgrid models do not currently consider the uncertain and long-term impacts of climate change when determining a set of design and operational decisions to minimize long-term costs or meet a resilience threshold. In this paper, we develop a novel scenario generation method that accounts for the uncertain effects of (i) climate change on variable renewable energy availability, (ii) extreme heat events on site load, and (iii) population and electrification trends on load growth. Additionally, we develop a two-stage stochastic programming extension of an existing microgrid design and dispatch optimization model to obtain uncertainty-informed and climate-resilient energy system decisions that minimizes long-term costs. Use of sample average approximation to validate our two case studies illustrates that the proposed methodology produces high-quality solutions that add resilience to systems with existing backup generation while reducing expected long-term costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1984

Space Station automation and autonomy

As the complexity of NASA's planned Space Station design grows, decision-making must be transferred from the crew to an onboard computer system devised for maximum man/machine interactions productivity. The Space Station's electrical power subsystem is presently taken as an exemplary case of design evolution from the manual, through the automated, to the fully autonomous control regimes.

Carlisle, R. F.↗
NASA NTRS1975

Cost consideration for aircraft configuration changes, 1

The costs of improvements in aircraft drag reduction design changes are outlined in the context of production decisions. A drag reduction design with increased airframe weight requires cost increases for direct labor, overhead and direct expenses, plus general and administrative expenses.

Tumlinson, R. R.↗