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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Measuring Topological Constraint Relaxation in Ring-Linear Polymer Blends

Polymers are an effective test bed for studying topological constraints in condensed matter due to a wide array of synthetically available chain topologies. When linear and ring polymers are blended together, emergent rheological properties are observed as the blend can be more viscous than either of the individual components. This emergent behavior arises since ring-linear blends can form long-lived topological constraints as the linear polymers thread the ring polymers. Here, in this work, we demonstrate how the Gauss linking integral can be used to efficiently evaluate the relaxation of topological constraints in ring-linear polymer blends. For majority-linear blends, the relaxation rate of topological constraints depends primarily on reptation of the linear polymers, resulting in the diffusive time τ d,R for rings of length N R blended with linear chains of length N l to scale as τ d,R ~ N$^2_R$N$^{3.4}_L$.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2000

The origin of intermediary metabolism

The core of intermediary metabolism in autotrophs is the citric acid cycle. In a certain group of chemoautotrophs, the reductive citric acid cycle is an engine of synthesis, taking in CO(2) and synthesizing the molecules of the cycle. We have examined the chemistry of a model system of C, H, and O that starts with carbon dioxide and reductants and uses redox couples as the energy source. To inquire into the reaction networks that might emerge, we start with the largest available database of organic molecules, Beilstein on-line, and prune by a set of physical and chemical constraints applicable to the model system. From the 3.5 million entries in Beilstein we emerge with 153 molecules that contain all 11 members of the reductive citric acid cycle. A small number of selection rules generates a very constrained subset, suggesting that this is the type of reaction model that will prove useful in the study of biogenesis. The model indicates that the metabolism shown in the universal chart of pathways may be central to the origin of life, is emergent from organic chemistry, and may be unique.

Non-NASA Center↗
DOE OSTI2025

LLGOMAX: Enhancing Industry-Standard Tools for AC Optimal Unit Commitment (CRADA Final Report)

This was a collaborative effort between Lawrence Livermore National Security, LLC ("LLNS"), as manager and operator of Lawrence Livermore National Laboratory ("LLNL") and ECCO International Inc. ("Participant"). The team designed and implemented a new approach for the Security-Constrained Alternating-Current Unit Commitment (SCACUC) problem. The SCACUC problem is a mathematical optimization problem that decides which generating units should be online and how much power should be produced (and consumed) at each point of the power grid. The decisions are made so as to minimize the total cost of supplying electricity while respecting technical constraints of the power grid, both under normal and emergency conditions. The team developed a solution for SCACUC as specified in the ARPA-E Grid Optimization Competition (GOC) Challenge 3, which put forth a forward-looking version of the problem, which many features not present in today’s electricity market specifications for SCACUC.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2009

A Methodology for Training International Space Station Crews to Respond to On-Orbit Emergencies

Most spaceflight crewmembers agree that emergency training is among the most important training they receive. If an emergency event occurs on-orbit crewmembers want to be able to rely on a thorough and proficient knowledge of emergency operations and procedures. The inherent complexity of ISS and the international nature of the onboard operations have resulted in emergency procedures that are complex by any measure; as a result, a very robust apparatus has been developed to give crewmembers initial training on emergency procedures and ensure proficiency up to (and even after) launch. One of the most important aspects of complex onboard operations in general, and emergency operations specifically, is learning how to coordinate roles and responsibilities with fellow crewmembers. A primary goal of NASA s emergency training program is to allow the crewmembers who will actually be together on-orbit to practice executing the emergency responses together before they fly. As with any operation that includes the use of software and hardware, the fidelity of the simulation environment is a critical element to successful training. The NASA training division has spent considerable time and effort to develop a simulator that addresses the most important aspects of emergency response, working within very difficult space and budgetary constraints.

Balmain, Clinton↗
DOE OSTI2024

DECA: Discrete Event inspired Cellular Automata for grain structure prediction in additive manufacturing

Microstructure largely dictates macroscopic material properties and is strongly affected by processing. Therefore, the simulation of microstructure evolution in response to thermal fields during processing is of significant interest within the computational materials science community. Additive manufacturing (AM) has emerged as a technique for producing complex geometries and unique microstructures. Yet, complex and rapid thermal cycles in AM pose computational challenges for existing microstructure models. This work proposes a discrete event inspired cellular automata (CA) approach, titled DECA, to accelerate simulation of grain structure evolution in AM. In contrast to conventional time-stepped CA models, this model directly solves the times capture events would take place allowing for stepping in events rather than time (a technique also found in the field of discrete-event simulation). In comparison to purely serial discrete-event models, DECA allows for temporary violation of the causality constraint, but detects and corrects these violations, leading to an emergent phenomenon dubbed causality rippling, in which previously calculated capture events are overwritten. The amount of repeated calculations, defined by the capture ratio, is taken as a measure of computational inefficiency, and the model parameters that affect this ratio are evaluated. The new DECA approach was found to be more computationally efficient than conventional time-stepped CA models while guaranteeing an accurate solution, which can only be achieved in the conventional models for vanishingly small time steps. Finally, opportunities for parallelization and scaling of the new approach are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Multi-objective materials bayesian optimization with active learning of design constraints: Design of ductile refractory multi-principal-element alloys

We report Bayesian Optimization (BO) has emerged as a powerful framework to efficiently explore and exploit materials design spaces. To date, most BO approaches to materials design have focused on the materials discovery problem as if it were a single expensive-to-query ‘black box’ in which the target is to optimize a single objective (i.e., material property or performance metric). Also, such approaches tend to be constraint agnostic. Here, we present a novel multi-information BO framework capable of actively learning materials design as a multiple objectives and constraints problem. We demonstrate this framework by optimally exploring a Refractory Multi-Principal-Element Alloy (MPEA) space, here specifically, the system Mo-Nb-Ti-V-W. The MPEAs are explored to optimize two density-functional theory (DFT) derived ductility indicators (Pugh’s Ratio and Cauchy pressure) while learning design constraints relevant to the manufacturing of high-temperature gas-turbine components. Alloys in the BO Pareto-front are analyzed using DFT to gain an insight into fundamental atomic and electronic underpinning for their superior performance, as evaluated within this framework.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Optimization of Energy Storage System Economics and Controls by Incorporating Battery Degradation Costs in REopt

The use of stationary electrochemical energy storage systems utilizing lithium-ion batteries has increased rapidly as the production scale and price for lithium-ion batteries has decreased. These energy storage systems are crucial for maintaining grid resiliency, especially for grids operating with high penetration of renewable energy generation assets or for with a variety of distributed energy generation and storage systems. One challenging factor for the development of battery energy storage systems is estimating the proper sizing, in terms of both power and energy, that minimizes total costs over the lifetime of the systems; this calculation is difficult in simple cases, where a battery is costed independently, but is extremely challenging when building loads and electrical generation by photovoltaic resources are also considered. REopt is a techoeconomic optimization tool developed by NREL to address these challenges. Previously, battery degradation has been priced by simply assuming a 10-year replacement schedule for battery systems. However, this does not account for varying degradation trends observed across real-world batteries, or allow for batteries to be operated in a degradation-aware manner that optimizes battery dispatch based on operating costs. This work incorporates a battery life model into REopt. This battery life model is simple, so that it may be solvable within the constrains of a mixed-integer linear optimization problem, but is fit to accelerated aging data recorded in the lab. To achieve the best possible accuracy for lifetime estimates given these constraints, parameters for the battery life model in REopt are estimated by fitting 20-year simulations of battery life after identifying state-space battery degradation model from accelerated aging data. Comparisons of battery life predicted in REopt and from the state-space battery degradation model to ensure validity of lifetime estimates made by REopt. Battery life and cost is optimized by controlling three decision to minimize system life cost: battery sizing, daily state-of-charge, and daily energy-throughput. The cost of battery degradation as a function of these control variables is then estimated assuming two possible maintenance strategies: replacement, where the entire battery system is replaced if cell reach an end-of-life capacity threshold; and augmentation, which establishes a fund to pay for continual purchase of new batteries to maintain the initial energy capacity of the system. These two strategies offer conservative (for replacement) and optimistic (for augmentation) bounds for total system cost. The degradation cost incurred by these strategies is then used to control battery dispatch decisions, operating the battery in a degradation-aware manner that maximizes battery lifetime while also providing energy when favorable. Because the mixed-integer linear program has perfect foresight of future energy needs, batteries with degradation costs are always operated using 'just-in-time' charging, which is unrealistic, as no energy is left in the storage system to perform other energy services or to serve as emergency back-up power. To combat this, an inequality constraint on the average annual state-of-charge is imposed, and the sensitivity of system cost to average stored energy, e.g., the cost of system resiliency, can be quantified. Analysis of results has several conclusions, for instance, oversizing of battery storage systems is not a cost burden when battery storage is an optimal solution, as any additional battery capacity can simply be utilized to avoid costs of purchasing energy from a utility.

battery↗
DOE OSTI2024

Consequences of minimal entanglement in bosonic field theories

In this paper, we study a recently discovered connection between scattering that minimally entangles and emergent symmetries. In a perturbative expansion, we have generalized the constraints of minimal entanglement scattering, beyond qubits, to general qudits of dimension d . Interestingly, projecting on any qubit subspaces, the constraints factorize, so that it is consistent to analyze minimal entanglement by looking at all such subspaces. We start by looking at toy models with two scalar fields, finding that minimal entanglement only allows quartic couplings which have instabilities at large field values and no symmetries. For the two Higgs doublet model, by considering H + H − → H + H − scattering, we show that minimal entanglement in this channel does not allow an interacting parameter point with enhanced symmetries. These results show that the connection between minimal entanglement and symmetries depends strongly on the scattering channels analyzed and we speculate on the potential resolutions. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Equivalence between Fermion-to-Qubit Mappings in two Spatial Dimensions

We argue that all locality-preserving mappings between fermionic observables and Pauli matrices on a two-dimensional lattice can be generated from the exact bosonization in Chen et al., whose gauge constraints project onto the subspace of the toric code with emergent fermions. Starting from the exact bosonization and applying Clifford finite-depth generalized local unitary transformation, we can achieve all possible fermion-to-qubit mappings (up to the re-pairing of Majorana fermions). In particular, we discover a new supercompact encoding using 1.25 qubits per fermion on the square lattice. We prove the existence of finite-depth quantum circuits to obtain fermion-to-qubit mappings with qubit-fermion ratios r = 1 + 1/2k for positive integers k, utilizing the trivialness of quantum cellular automata in two spatial dimensions. Also, we provide direct constructions of fermion-to-qubit mappings with ratios arbitrarily close to 1. When the ratio reaches 1, the fermion-to-qubit mapping reduces to the one-dimensional Jordan-Wigner transformation along a certain path in the two-dimensional lattice. Finally, we explicitly demonstrate that the Bravyi-Kitaev superfast simulation, the Verstraete-Cirac auxiliary method, Kitaev’s exactly solved model, the Majorana loop stabilizer codes, and the compact fermion-to-qubit mapping can all be obtained from the exact bosonization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1985

Space Station man-machine automation trade-off analysis

The man machine automation tradeoff methodology presented is of four research tasks comprising the autonomous spacecraft system technology (ASST) project. ASST was established to identify and study system level design problems for autonomous spacecraft. Using the Space Station as an example spacecraft system requiring a certain level of autonomous control, a system level, man machine automation tradeoff methodology is presented that: (1) optimizes man machine mixes for different ground and on orbit crew functions subject to cost, safety, weight, power, and reliability constraints, and (2) plots the best incorporation plan for new, emerging technologies by weighing cost, relative availability, reliability, safety, importance to out year missions, and ease of retrofit. A fairly straightforward approach is taken by the methodology to valuing human productivity, it is still sensitive to the important subtleties associated with designing a well integrated, man machine system. These subtleties include considerations such as crew preference to retain certain spacecraft control functions; or valuing human integration/decision capabilities over equivalent hardware/software where appropriate.

Zimmerman, W. F.↗
NASA NTRS1996

The Influence of Future Command, Control, Communications, and Computers (C4) on Doctrine and the Operational Commander's Decision-Making Process

Future C4 systems will alter the traditional balance between force and information, having a profound influence on doctrine and the operational commander's decision making process. The Joint Staff's future vision of C4 is conceptualized in 'C4I for the Warrior' which envisions a joint C4I architecture providing timely sensor to shoot information direct to the warfighter. C4 system must manage and filter an overwhelming amount of information; deal with interoperability issues; overcome technological limitations; meet emerging security requirements; and protect against 'Information Warfare.' Severe budget constraints necessitate unified control of C4 systems under singular leadership for the common good of all the services. In addition, acquisition policy and procedures must be revamped to allow new technologies to be fielded quickly; and the commercial marketplace will become the preferred starting point for modernization. Flatter command structures are recommended in this environment where information is available instantaneously. New responsibilities for decision making at lower levels are created. Commanders will have to strike a balance between exerting greater control and allowing subordinates enough flexibility to maintain initiative. Clearly, the commander's intent remains the most important tool in striking this balance.

Mayer, Michael G.↗
NASA NTRS2001

The AutoBayes Program Synthesis System: System Description

AUTOBAYES is a fully automatic program synthesis system for the statistical data analysis domain. Its input is a concise description of a data analysis problem in the form of a statistical model; its output is optimized and fully documented C/C++ code which can be linked dynamically into the Matlab and Octave environments. AUTOBAYES synthesizes code by a schema-guided deductive process. Schemas (i.e., code templates with associated semantic constraints) are applied to the original problem and recursively to emerging subproblems. AUTOBAYES complements this approach by symbolic computation to derive closed-form solutions whenever possible. In this paper, we concentrate on the interaction between the symbolic computations and the deductive synthesis process. A statistical model specifies for each problem variable (i.e., data or parameter) its properties and dependencies in the form of a probability distribution, A typical data analysis task is to estimate the best possible parameter values from the given observations or measurements. The following example models normal-distributed data but takes prior information (e.g., from previous experiments) on the data's mean value and variance into account.

Fischer, Bernd↗
NASA NTRS2007

High Altitude Long Endurance UAV Analysis of Alternatives and Technology Requirements Development

An Analysis of Alternatives and a Technology Requirements Study were conducted for two mission areas utilizing various types of High Altitude Long Endurance (HALE) Unmanned Aerial Vehicles (UAV). A hurricane science mission and a communications relay mission provided air vehicle requirements which were used to derive sixteen potential HALE UAV configurations, including heavier-than-air (HTA) and lighter-than-air (LTA) concepts with both consumable fuel and solar regenerative propulsion systems. A HTA diesel-fueled wing-body-tail configuration emerged as the preferred concept given near-term technology constraints. The cost effectiveness analysis showed that simply maximizing vehicle endurance can be a sub-optimum system solution. In addition, the HTA solar regenerative configuration was utilized to perform both a mission requirements study and a technology development study. Given near-term technology constraints, the solar regenerative powered vehicle was limited to operations during the long days and short nights at higher latitudes during the summer months. Technology improvements are required in energy storage system specific energy and solar cell efficiency, along with airframe drag and mass reductions to enable the solar regenerative vehicle to meet the full mission requirements.

Nickol, Craig L.↗
DOE OSTI2020

A Computational Theory for the Emergence of Grammatical Categories in Cortical Dynamics

A general agreement in psycholinguistics claims that syntax and meaning are unified precisely and very quickly during online sentence processing. Although several theories have advanced arguments regarding the neurocomputational bases of this phenomenon, we argue that these theories could potentially benefit by including neurophysiological data concerning cortical dynamics constraints in brain tissue. In addition, some theories promote the integration of complex optimization methods in neural tissue. In this paper we attempt to fill these gaps introducing a computational model inspired in the dynamics of cortical tissue. In our modeling approach, proximal afferent dendrites produce stochastic cellular activations, while distal dendritic branches–on the other hand–contribute independently to somatic depolarization by means of dendritic spikes, and finally, prediction failures produce massive firing events preventing formation of sparse distributed representations. The model presented in this paper combines semantic and coarse-grained syntactic constraints for each word in a sentence context until grammatically related word function discrimination emerges spontaneously by the sole correlation of lexical information from different sources without applying complex optimization methods. By means of support vector machine techniques, we show that the sparse activation features returned by our approach are well suited—bootstrapping from the features returned by Word Embedding mechanisms—to accomplish grammatical function classification of individual words in a sentence. In this way we develop a biologically guided computational explanation for linguistically relevant unification processes in cortex which connects psycholinguistics to neurobiological accounts of language. We also claim that the computational hypotheses established in this research could foster future work on biologically-inspired learning algorithms for natural language processing applications.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1971

Concepts and system design of a space emergency re-entry vehicle.

Discussion of the spectrum of remedial concepts and realistic mission constraints. A vehicle design is presented which is offered as the 'best' solution among a number of alternative designs in terms of its cost effectiveness. The probability of the safe reentry and recovery of one to three stranded astronauts is 0.80. The vehicle is symmetrical and lenticular in shape, and exhibits a modest lift-to-drag ratio of 0.5, allowing it to reenter a two-skip trajectory with minimal gravity forces on the astronauts. Attitude control, voice and beacon communication, and impact attenuation are also provided. The vehicle could be delivered in a docked position on the Apollo Applications Program multiple docking adapter.

Huang, C. J.↗
NASA NTRS2019

Emerging Aviation Trends in ATD-2 and Vector for Future Innovation

This briefing discusses the constraints of the Northeast Corridor (NEC), the increasing predictability that can be achieved by leveraging digital assets (e.g., EOBT), and the challenges of a multi-airport scenario and the use of TOS alternative routes. It further describes the potential of near-term digital asset expansion and near real-time predictive analytics to generate innovative solutions.

Capps, Al↗
NASA NTRS1990

Requirements for long-life mechanical cryocoolers for space applications

The growing demand for long wavelength infrared and submillimeter imaging instruments for space observational applications, together with the emergence of the multiyear life Oxford University Stirling cycle cooler, has led to a rapidly expanding near term commitment to mechanical cryocoolers throughout the subkelvin to 150 K temperature range for long-life space missions. To satisfy this growing commitment, emerging cryocoolers must successfully address not only the input power, cooling power, and mass constraints of the spacecraft and instruments, but also the broad array of complex interface requirements that critically affect successful integration to the sensitive instrument detectors. Generic requirements are presented for each of the cryocooler requirement areas, which are then contrasted with the projected capabilities of emerging space cryocoolers. The degree of match is used to highlight both the strengths of existing technologies and the areas in need of increased development.

Ross, R. G., Jr.↗
DOE OSTI2022

Emerging Trends and Systemic Issues Influencing Today’s U.S. Electric Grid

With increasing shifts from vertically integrated to horizontally structured operations and from centralized to distributed electric power delivery, today’s electric power grid (the “grid”) operators and designers face the challenge of creating an architecture that accommodates a host of diverse requirements. The grid’s modes of operation must address concerns of reliability and stability, new deployments of renewable energy sources, threats from cyber-attacks and natural disasters, and increasingly distributed system operations. Grid modernization calls for a reliable, affordable, sustainable, agile, secure, and resilient grid. However, the modernization of the U.S. power grid is hampered by mounting complexity and diverging objectives from owners and operators and is consequently risky and fraught with potential missteps. Flawed architecture, design, and implementation will lead to stranded investments and lost opportunities. A principled approach to minimize risk and develop a robust grid of the future is to begin with a sound architecture for the grid to inform the design process. Architecture development starts with the context of influencing factors that provide constraints as well as driving goals. This report provides the context of emerging trends and cross-cutting systemic issues in the U.S. electric power grid and serves as a vital input for grid architecture development.

24 POWER TRANSMISSION AND DISTRIBUTION↗