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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Implementation Plan for Combined Heat and Power Systems VOLTTRON Controller: Performance Monitoring and Real-Time Commissioning Algorithm Verification

Building-integrated cooling, heating, and power (CHP) systems are more efficient than conventional systems at providing local power and thermal energy, and favorable fuel prices are bound to spur their increased adoption. However, to realize the full benefit of the CHP systems, we must ensure persistence of energy efficient operations. Much of the inefficiency in the current building operations can be eliminated by use of automated performance monitoring (PM), real-time commissioning verification (CxV) and automated fault detection and diagnostic (AFDD) tools. Automation can help system operators make intelligent decisions. Remote and continuous monitoring of system conditions and performance will enable better management and integration of CHP with existing building systems. Continuous PM, real-time CxV, and AFDD could alleviate burdens for operations staff, enhance operations and maintenance (O&M), and improve reliability of building and CHP systems. To address the O&M challenges and to provide a means to maximize the rate-of-return of building-integrated CHP systems, the Building Technologies Office (BTO) within the U.S. Department of Energy’s (DOE’s) Office of Energy Efficiency and Renewable Energy (EERE) initiated a project to design, develop, and field test a VOLTTRON™-based supervisory controller and associated open-source algorithms. These algorithms will ensure real-time optimal operation of a building-integrated CHP system, support electric grid reliability, and lead to achieving the goal of clean, efficient, reliable, and affordable next-generation integrated energy system. Previous report listed the components for which PM, real-time CxV, and AFDD algorithms will be developed, how the algorithms will be tested, and the metrics that will be used to validate the algorithms and their ease of deployment. Deployment of these algorithms in the field will result in a reduction in energy consumption of between 10% and 20% (for both CHP and conventional building systems). This report builds upon the previous report by detailing the process by which PNNL will implement performance monitoring and real-time commissioning algorithms for CHP systems in conjunction with the use of the VOLTTRON CHP economic dispatch agent in host facilities.

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

Uncrewed Lunar Surface Operations and Support Activities

A sustained human presence on the surface of the Moon and future missions to Mars require increased independence from surface crews and Earth-based mission control to operate efficiently, safely, and reliably. The number of astronauts and the availability of the surface crew to perform tasks will be limited, and extravehicular activities are burdensome and time-consuming. A balance of crewed and uncrewed surface operations will maximize crew exploration time by reducing their time dedicated to routine maintenance and support tasks. Certain sustaining activities that consume valuable crew time and preparation tasks such as staging and prepositioning equipment and materials can be performed without the crew, either before their arrival on the lunar surface or after their departure, thus improving task efficiency and mission effectiveness. This paper will define uncrewed operations and support activities and examine the functions, features, and capabilities that support sustained human and robotic surface operations. It will also discuss the extreme environmental challenges and the complexities associated with the development and operation of autonomous systems, as well as some suggested methods, techniques, and tools to overcome these challenges.

Lunar↗
DOE OSTI2016

Co-Optimization of Fuels and Engines

The Co-Optimization of Fuels and Engines (Co-Optima) initiative is a new DOE initiative focused on accelerating the introduction of affordable, scalable, and sustainable biofuels and high-efficiency, low-emission vehicle engines. The simultaneous fuels and vehicles research and development (R&D) are designed to deliver maximum energy savings, emissions reduction, and on-road vehicle performance. The initiative's integrated approach combines the previously independent areas of biofuels and combustion R&D, bringing together two DOE Office of Energy Efficiency & Renewable Energy research offices, ten national laboratories, and numerous industry and academic partners to simultaneously tackle fuel and engine research and development (R&D) to maximize energy savings and on-road vehicle performance while dramatically reducing transportation-related petroleum consumption and greenhouse gas (GHG) emissions. This multi-year project will provide industry with the scientific underpinnings required to move new biofuels and advanced engine systems to market faster while identifying and addressing barriers to their commercialization. This project's ambitious, first-of-its-kind approach simultaneously tackles fuel and engine innovation to co-optimize performance of both elements and provide dramatic and rapid cuts in fuel use and emissions. This presentation provides an overview of the initiative and reviews recent progress focused on both advanced spark-ignition and compression-ignition approaches.

09 BIOMASS FUELS↗
DOE OSTI2016

A concentrated solar cavity absorber with direct heat transfer through recirculating metallic particles

A recirculating flow solar particle cavity absorber (receiver) is modeled to investigate the flow behavior and heat transfer characteristics of a novel developing concept. It features a continuous recirculating flow of non-reacting metallic particles (black silicon carbide) with air which are used as a thermal enhancement medium. The aim of the present study is to numerically investigate the thermal behavior and flow characteristics of the proposed concept. The proposed solar particle receiver is modeled using two phase discrete particle model (DPM), RNG k-flow model and discrete ordinate (DO) radiation model. Numerical analysis is carried out considering a solar receiver with only air and the mixture of non-reacting particles and air as a heat transfer as well as heat carrying medium. The parametric investigation is conducted considering the incident solar flux on the receiver aperture and changing air flow rate and recirculation rate inside the receiver. A stand-alone feature of the recirculating flow solar particle receiver concept is that the particles are directly exposed to concentrated solar radiation monotonously through recirculating flow inside the receiver and results in efficient irradiation absorption and convective heat transfer to air that help to achieve high temperature air and consequently increase in thermal efficiency. This paper presents, results from the developed concept and highlights its flow behavior and potential to enhance the heat transfer from metallic particles to air by maximizing heat carrying capacity of the heat transfer medium. The imposed milestones for the present system will be helpful to understand the radiation absorption mechanism of the particles in a recirculating flow based receiver, the thermal transport between the particles, the air and the cavity, and the fluid dynamics of the air and particle in the cavity.

14 SOLAR ENERGY↗
DOE OSTI2021

Resilient NdFeB magnet recycling under the impacts of COVID-19 pandemic: Stochastic programming and Benders decomposition

Neodymium-iron-boron (NdFeB) magnets are the most powerful magnets per unit volume sold in the commercial market. Despite the increasing demand for clean energy applications such as electric vehicles and wind turbines, disruptive events including the COVID-19 pandemic have caused significant uncertainties in the supply and demand for NdFeB magnets. Therefore, this study aims to alleviate the risk of supply shortage for NdFeB magnets and the containing critical materials, rare-earth elements (REEs), through the development of a resilient reverse supply chain and logistics network design. We develop scenarios to model the unique impact of the COVID-19 pandemic on the proposed business, incorporating both disruption intensity and recovery rate. We formulate a chance-constrained two-stage stochastic programming model to maximize the profit while guaranteeing the network resiliency against disruption risks. To solve the problem in large-scale instances, we develop an efficient Benders decomposition algorithm that reduces the computational time by 98.5% on average compared to the default CPLEX algorithm. When applied to the United States, the model suggests the optimal facility locations, processing capacities, inventory levels, and material flows for NdFeB magnet recyclers that could meet 99.7% of the demand. To the best of our knowledge, this study is the first to incorporate the impacts of the COVID-19 pandemic to design a resilient NdFeB magnet recycling supply chain and logistics network, leveraging risk-averse stochastic programming.

42 ENGINEERING↗
DOE OSTI2015

Elucidation of perovskite film micro-orientations using two-photon total internal reflectance fluorescence microscopy

The emergence of efficient hybrid organic-inorganic perovskite photovoltaic materials has caused the rapid development of a variety of preparation and processing techniques designed to maximize their performance. As processing methods continue to emerge, it is important to understand how the optical properties of these materials are affected on a microscopic scale. Here polarization resolved two-photon total internal reflectance microscopy (TIRFM) was used to probe changes in transition dipole moment orientation as a function of thermal annealing time in hybrid organic-inorganic lead iodide based perovskite (CH 3 NH 3 PbI 3 ) thin films on glass. These results show that as thermal annealing time is increased the distribution of transition moments pointing out-of-plane decreases in favor of forming areas with increased in-plane orientations. As a result, it was also shown through the axial sensitivity of TIRFM that the surface topography is manifested in the signal intensity and can be used to survey aspects of morphology in coincidence with the optical properties of these films.

36 MATERIALS SCIENCE↗
DOE OSTI2021

CIGS photovoltaics: reviewing an evolving paradigm

Copper indium selenide chalcopyrite-structure alloys with gallium (CIGS) are unique among the highest performing photovoltaic (PV) semiconductor technologies. They are structurally disordered, nonstoichiometric materials that have been engineered to achieve remarkably low bulk nonradiative recombination levels. Nevertheless, their performance can be further improved. This review adopts a fundamental thermodynamic perspective to comparatively assess the root causes of present limitations on CIGS PV performance. The topics of selectivity and passivation of contacts to CIGS and its multinary alloys are covered, highlighting pathways to maximizing the electrochemical potential between those contacts under illumination. Further, an overview of absorber growth methods and resulting properties is also provided. We recommend that CIGS researchers consider strategies that have been successfully implemented in the more mature wafer-based GaAs and Si PV device technologies, based on the paradigm of an idealized PV device design using an isotropic absorber with minimal nonradiative recombination, maximal light trapping, and both electron-selective and hole-selective passivated contacts. We foresee that CIGS technology will reach the 25% efficiency level within the next few years through enhanced collection and reduced recombination. To significantly impact power-generation applications, cost-effective, manufacturable solutions are also essential.

14 SOLAR ENERGY↗
DOE OSTI2017

Technologies for Prolonging Cardiac Implantable Electronic Device Longevity

Prolonged longevity of cardiac implantable electronic devices (CIEDs) is needed not only as a passive response to match the prolonging life expectancy of patient recipients, but will also actively prolong their life expectancy by avoiding/deferring the risks (and costs) associated with device replacement. CIEDs are still exclusively powered by nonrechargeable primary batteries, and energy exhaustion is the dominant and an inevitable cause of device replacement. The longevity of a CIED is thus determined by the attrition rate of its finite energy reserve. The energy available from a battery depends on its capacity (total amount of electric charge), chemistry (anode, cathode, and electrolyte), and internal architecture (stacked plate, folded plate, and spiral wound). The energy uses of a CIED vary and include a background current for running electronic circuitry, periodic radiofrequency telemetry, high‐voltage capacitor reformation, constant ventricular pacing, and sporadic shocks for the cardiac resynchronization therapy defibrillators. The energy use by a CIED is primarily determined by the patient recipient's clinical needs, but the energy stored in the device battery is entirely under the manufacturer's control. A larger battery capacity generally results in a longer‐lasting device, but improved battery chemistry and architecture may allow more space‐efficient designs. Armed with the necessary technical knowledge, healthcare professionals and purchasers will be empowered to make judicious selection on device models and maximize the utilization of all their energy‐saving features, to prolong device longevity for the benefits of their patients and healthcare systems.

LAU, ERNEST W.↗
DOE OSTI2022

Pareto Optimal and Dual-Objective Geometric and Structural Design of an Underwater Kite for Closed-Loop Flight Performance

This paper presents the formulation and results for a control-aware optimization of the combined geometric and structural design of an energy-harvesting underwater kite. Because kite-based energy-harvesting systems, both airborne and underwater, possess strong coupling between closed-loop flight control, geometric design, and structural design, consideration of all three facets of the design within a single codesign framework is highly desirable. However, while prior literature has addressed one or two attributes of the design at a time, this work constitutes the first comprehensive effort aimed at addressing all three. In particular, focusing on the goals of power maximization and mass minimization, we present a codesign formulation that fuses a geometric optimization tool, structural optimization tool, and closed-loop flight efficiency map. The resulting integrated codesign tool is used to address two mathematical optimization formulations that exhibit subtle differences: a Pareto optimal formulation and a dual-objective formulation that focuses on a weighted power-to-mass ratio as the techno-economic metric of merit. Further, based on the resulting geometric and structural designs, using a mediumfidelity closed-loop simulation tool, the proposed formulation is shown to achieve more than three times the powerto-mass ratio of a previously published, unoptimized benchmark design.

42 ENGINEERING↗
DOE OSTI2020

Construction-Scale Concrete Additive Manufacturing and its Application in Infrastructure Energy Storage

Construction is filled with labor intensive, hazardous, and often wasteful processes. It is also an enormous industry, so improvements in efficiency could have a tremendous economic impact. Construction-scale additive manufacturing is one path toward achieving those improvements. In this paper, a construction-scale additive manufacturing system, called Sky-BAAM, is presented. In addition to possibly leading to more energy-efficient construction practices, leveraging additive manufacturing in construction opens the solution space to more energy efficient building design. One such design, the EMPOWER wall, is also presented in this paper. The exterior of the wall is shaped to maximize heat transfer, while acting as form work for an internal energy-storage system. This allows energy to be stored in the wall during off-peak times and retrieved during peak periods.

Atkins, Celeste↗
DOE OSTI2014

Biochemical and Structural Studies of NADH-Dependent FabG Used To Increase the Bacterial Production of Fatty Acids under Anaerobic Conditions

Major efforts in bioenergy research have focused on producing fuels that can directly replace petroleum-derived gasoline and diesel fuel through metabolic engineering of microbial fatty acid biosynthetic pathways. Typically, growth and pathway induction are conducted under aerobic conditions, but for operational efficiency in an industrial context, anaerobic culture conditions would be preferred to obviate the need to maintain specific dissolved oxygen concentrations and to maximize the proportion of reducing equivalents directed to biofuel biosynthesis rather than ATP production. A major concern with fermentative growth conditions is elevated NADH levels, which can adversely affect cell physiology. The purpose of this study was to identify homologs of Escherichia coli FabG, an essential reductase involved in fatty acid biosynthesis, that display a higher preference for NADH than for NADPH as a cofactor. Four potential NADH-dependent FabG variants were identified through bioinformatic analyses supported by crystallographic structure determination (1.3- to 2.0-Å resolution). In vitro assays of cofactor (NADH/NADPH) preference in the four variants showed up to ~35-fold preference for NADH, which was observed with the Cupriavidus taiwanensis FabG variant. In addition, FabG homologs were overexpressed in fatty acid- and methyl ketone-overproducing E. coli host strains under anaerobic conditions, and the C. taiwanensis variant led to a 60% higher free fatty acid titer and 75% higher methyl ketone titer relative to the titers of the control strains. With further engineering, this work could serve as a starting point for establishing a microbial host strain for production of fatty acid-derived biofuels (e.g., methyl ketones) under anaerobic conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

HyMARC Seedling: Optimized Hydrogen Adsorbents via Machine Learning and Crystal Engineering

This final report is presented in two parts: In Part 1, the H 2 capacities of a diverse set of 918,734 metal-organic frameworks (MOFs) sourced from 19 databases is predicted via machine learning (ML). Using only 7 structural features as input, ML identifies 8,282 MOFs with the potential to exceed the capacities of state-of-the-art materials. The identified MOFs are predominantly hypothetical compounds having low densities (<0.31 g/cm3) in combination with high surface areas (>5,300 m2/g), void fractions ($0.90), and pore volumes (>3.3 cm3/g). The relative importance of the input features are characterized, and dependencies on the ML algorithm and training set size are quantified. The most important features for predicting H 2 uptake are pore volume (for gravimetric capacity) and void fraction (for volumetric capacity). The ML models are available on the web, allowing for rapid and accurate predictions of the hydrogen capacities of MOFs from limited structural data; the simplest models require only a single crystallographic feature. In part 2, ways to improve the poor powder packing density of MOFs is discussed. More specifically, a strategy that improves packing efficiency and volumetric hydrogen gas storage density dramatically through engineered morphologies and controlled-crystal size distributions is presented that holds promise for maximizing storage capacity for a given MOF. The packing density improvement, demonstrated for the benchmark sorbent MOF-5, leads to a significant enhancement of volumetric hydrogen storage performance relative to commercial MOF-5. System model projections demonstrate that engineering of crystal morphology/size or use of a bimodal distribution of cubic crystal sizes in tandem with system optimization can surpass the 25 g/L volumetric capacity of a typical 700 bar compressed storage system and exceed the DOE targets 2020 volumetric capacity (30 g/L). Finally, a critical link between improved powder packing density and reduced damage upon compaction is revealed leading to sorbents with both high surface area and high density.

08 HYDROGEN↗
NASA NTRS1978

Airfoil design by numerical optimization using a minicomputer

A computer program developed for the automated design of low speed airfoils utilizes a generalized Joukowski method for aerodynamic analysis coupled with a conjugate gradient, penalty function, numerical optimization algorithm to give an efficient calculation technique for use with minicomputers. The program designs airfoils with a prescribed pressure distribution as well as those which minimize or maximize some aerodynamic force coefficient. At present the method is restricted to inviscid, incompressible flow. A typical design problem will execute in 4.5 hr on an HP 9830 minicomputer.

Hicks, R. M.↗
NASA NTRS1985

A sequential linear optimization approach for controller design

A linear optimization approach with a simple real arithmetic algorithm is presented for reliable controller design and vibration suppression of flexible structures. Using first order sensitivity of the system eigenvalues with respect to the design parameters in conjunction with a continuation procedure, the method converts a nonlinear optimization problem into a maximization problem with linear inequality constraints. The method of linear programming is then applied to solve the converted linear optimization problem. The general efficiency of the linear programming approach allows the method to handle structural optimization problems with a large number of inequality constraints on the design vector. The method is demonstrated using a truss beam finite element model for the optimal sizing and placement of active/passive-structural members for damping augmentation. Results using both the sequential linear optimization approach and nonlinear optimization are presented and compared. The insensitivity to initial conditions of the linear optimization approach is also demonstrated.

Horta, L. G.↗
NASA NTRS2018

Differential Adaptive Stress Testing of Airborne Collision Avoidance Systems

The next-generation Airborne Collision Avoidance System (ACAS X) is currently being developed and tested to replace the Traffic Alert and Collision Avoidance System (TCAS) as the next international standard for collision avoidance. To validate the safety of the system, stress testing in simulation is one of several approaches for analyzing near mid-air collisions (NMACs). Understanding how NMACs can occur is important for characterizing risk and informingdevelopment of the system. Recently, adaptive stress testing (AST) has been proposed as a way to find the most likely path to a failure event. The simulation-based approach accelerates search by formulating stress testing as a sequential decision process then optimizing it using reinforcement learning. The approach has been successfully applied to stress test a prototype of ACAS Xin various simulated aircraft encounters. In some applications, we are not as interestedin the system's absolute performance as its performance relative to another system. Such situations arise, for example, during regression testing or when deciding whether a new system should replace an existing system. In our collision avoidance application, we are interested in finding cases where ACAS X fails but TCAS succeeds in resolving a conflict. Existing approaches do not provide an efficient means to perform this type of analysis. This paper extends the AST approach to differential analysis by searching two simulators simultaneously and maximizing the difference between their outcomes. We call this approach differential adaptive stress testing (DAST). We apply DAST to compare a prototype of ACAS X against TCAS and show examples of encounters found by the algorithm.

Lee, Ritchie↗
NASA NTRSDate not supplied

Statistical Engineering

This webinar provides an overview of the International Statistical Engineering Association (ISEA), and it illustrates the practice of statistical engineering at NASA. ISEA was formed to promote the study of how successful data-based problem-solving methods are leveraged to realize innovative opportunities and solve problems sustainably. ISEA is comprised of statisticians, engineers, scientists, and other professionals that exchange ideas and experiences in the development and application of statistical engineering theories. ISEA is building the body of knowledge of the statistical engineering discipline with a particular focus on improving academic preparation for tackling complex problems. Over the past 15 years, the practice of statistical engineering has gained recognition within NASA by spurring innovation and efficiency, and it has demonstrated significant impact. Aerospace research and development benefits from an application-focused statistical engineering perspective to accelerate learning, maximize knowledge, ensure strategic resource investment, and inform data-driven decisions. The second portion of this presentation provides an overview of infusing statistical engineering at NASA through pioneering case studies in aeronautics, space exploration, and atmospheric science.

Peter A Parker↗
DOE OSTI2013

R and D of crystal scintillators from enriched isotopes for high sensitivity double β decay experiments

Experiments to search for neutrinoless double beta decay enters to a new phase when a sensitivity on the level of T{sub 1/2}∼10{sup 26}−10{sup 28} yr is required. Scintillating low temperature detectors possess important properties required for high-sensitivity double beta decay experiments: presence of elements of interest, high energy resolution and detection efficiency, low level of background thanks to excellent particle discrimination ability. High concentration of isotope of interest and as low as possible radioactive contamination are important requirements to crystal scintillators. Other crucial issues are maximal output of detectors and minimal loss of enriched materials. Prospects of several scintillation materials, enriched in isotopes promising for double beta decay experiments, are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Cohesive phase-field fracture and a PDE constrained optimization approach to fracture inverse problems

In recent years there has been a proliferation of modeling techniques for forward predictions of crack propagation in brittle materials, including: phase-field/gradient damage models, peridynamics, cohesive-zone models, and G/XFEM enrichment techniques. However, progress on the corresponding inverse problems has been relatively lacking. Taking advantage of key features of existing modeling approaches, we propose a parabolic regularization of Barenblatt cohesive models which borrows extensively from previous phase-field and gradient damage formulations. An efficient explicit time integration strategy for this type of nonlocal fracture model is then proposed and justified. In addition, we present a C++ computational framework for computing in- put parameter sensitivities efficiently for explicit dynamic problems using the adjoint method. This capability allows for solving inverse problems involving crack propagation to answer interesting engineering questions such as: 1) what is the optimal design topology and material placement for a heterogeneous structure to maximize fracture resistance, 2) what loads must have been applied to a structure for it to have failed in an observed way, 3) what are the existing cracks in a structure given various experimental observations, etc. In this work, we focus on the first of these engineering questions and demonstrate a capability to automatically and efficiently compute optimal designs intended to minimize crack propagation in structures.

97 MATHEMATICS AND COMPUTING↗