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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

[High Pressure Gas Tanks]

Four high-pressure gas tanks, the basis of this study, were especially made by a private contractor and tested before being delivered to NASA Kennedy Space Center. In order to insure 100% reliability of each individual tank the staff at KSC decided to again submit the four tanks under more rigorous tests. These tests were conducted during a period from April 10 through May 8 at KSC. This application further validates the predictive safety model for accident prevention and system failure in the testing of four high-pressure gas tanks at Kennedy Space Center, called Continuous Hazard Tracking and Failure Prediction Methodology (CHTFPM). It is apparent from the variety of barriers available for a hazard control that some barriers will be more successful than others in providing protection. In order to complete the Barrier Analysis of the system, a Task Analysis and a Biomechanical Study were performed to establish the relationship between the degree of biomechanical non-conformities and the anomalies found within the system on particular joints of the body. This relationship was possible to obtain by conducting a Regression Analysis to the previously generated data. From the information derived the body segment with the lowest percentage of non-conformities was the neck flexion with 46.7%. Intense analysis of the system was conducted including Preliminary Hazard Analysis (PHA), Failure Mode and Effect Analysis (FMEA), and Barrier Analysis. These analyses resulted in the identification of occurrences of conditions, which may be becoming hazardous in the given system. These conditions, known as dendritics, may become hazards and could result in an accident, system malfunction, or unacceptable risk conditions. A total of 56 possible dendritics were identified. Work sampling was performed to observe the occurrence each dendritic. The out of control points generated from a Weighted c control chart along with a Pareto analysis indicate that the dendritics "Personnel not Wearing Proper Protective and Hose/tubing located in high-traffic area" which account for 59.18% of total dendritic frequency need to be addressed to reduce the chance of a hazard from occurring. However, the occurrences of some dendritics are more important than others. As a result immediate, from a Weighted c perspective, corrective action should be taken to ameliorate the cause of the Class A dendritic "Personnel located under suspended or moving loads" rather than just the most commonly occurring dendritics. In any case the vast majority of data obtained indicates that testing operations possess a relatively high degree of safety.

Quintana, Rolando↗
NASA NTRS2024

Leveraging the Gravity Field Spectrum for Icy Satellite Interior Structure Determination: The case of Europa with the Europa Clipper Mission

Understanding the interior structures of icy moons is pivotal for addressing their origins and habitability. We introduce an approach employing the gravity field spectrum as an additional constraint for the inversion of differentiated icy bodies' interior structures. After developing the general methodology, we apply it to Europa, utilizing the predicted measurement capability of NASA's Europa Clipper mission, and we prove its effectiveness in resolving key geophysical parameters. Notably, we show that using the gravity field spectrum in combination with the mass and moment of inertia of the body allows us to estimate, depending on the considered end-member interior structure, the hydrosphere thickness with 4–20 km uncertainty and reliably determine the seafloor maximum topographic range and elastic thickness to within 100–600 m and 5–15 km, respectively, together with the power–degree relationship of the seafloor topography. We also show that the proposed method allows us to determine the density of the silicate mantle and the radius of the core to within 0.25 g cc −1 and 50 km, respectively.

G. Cascioli↗
DOE OSTI2022

Analysis of SCALE Criticality and Sensitivity Calculations for Reflected HEU Cylinders [Slides]

The SCALE code package offers multiple nuclear data libraries supporting Monte Carlo transport, with sensitivity and uncertainty methods derived from MC transport solutions. Several libraries are multigroup, which introduce bias differing by system. Previous work has shown poor S/U results in several reflector materials: ICSBEP benchmark HMF-084 was selected to analyze biases and S/U method applicability to a variety of reflectors. Prior and ongoing work found inaccuracies in CSAS and TSUNAMI results, which were further investigated utilizing the HEU-MET-FAST-084 ICSBEP critical benchmark, chosen for its geometrical simplicity and variety of reflector materials. Perturbation of reflector thickness across various reflector materials allowed for an assortment of materials is to be tested swiftly for each sequence and method. Observation was an increasing bias of MG $k_{eff}$ relative to CE, in both direction and magnitude. IFP produced extremely reliable results. >85% of CLUTCH cases were found satisfactory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Tailoring composition and deformation modes at the microstructural level for next generation low-cost high-strength austenitic stainless steels

The objective of this project is to enable deliberate development of cost-effective, hydrogen resistant alloys by establishing detailed relationships specific to the effects of alloy composition, short-range order (SRO), and microsegregation in the presence of hydrogen on the transition between homogeneous deformation and localized plasticity in shear bands. In collaboration with the International Institute for Carbon-Neutral Energy Research, I2CNER, at Kyushu University in Japan, we conceptualized, designed, and manufactured four austenitic alloys that maintain corrosion resistance and ensure lower cost relative to baseline commercial alloys. The mechanical properties and deformation modes of the novel alloys (KU alloys) were assessed in the presence of hydrogen (H). Correlations between composition and performance revealed that two of the KU alloys are suitable replacements for 316 steel, while another is a viable replacement for 304 steel at room temperature. We found that, in the presence of other austenite stabilizing elements namely Mn and N, replacing Ni with Cu does not lead to martensite formation as has been previously reported.1–3 Furthermore, we found that the addition of Cu leads to an earlier onset of multiple slip resulting in an relative earlier onset of a higher work hardening rate (WHR). Greater understanding of the relationships between alloy composition and SRO required the development of a novel advanced electron diffraction methodology to characterize SRO in complex FCC alloys. This innovative approach, which combines fluctuation and correlation analyses of diffuse-scattering signals, successfully differentiated between SRO and long-range ordering (LRO). Further investigations into annealed austenitic stainless steels could provide insights into manipulating SRO and its effects on material properties. Atomistic simulations provided understanding of SRO behavior that was difficult to capture experimentally. This project created the first spin cluster expansion model that is able to capture and describe SRO effects in Fe-Ni-Cr FCC alloys, accounting for the non-negligible effects of magnetism. An automated computational workflow was established to provide reliable predictions of SRO in Fe-Ni-Cr austenitic alloys, both with and without the presence of H atoms. Analysis of the propensity for SRO in Fe-Ni-Cr alloys revealed that H tends to cluster with specific, well-defined SRO domains. The computational framework is general purpose and can be extended to realistic stainless steels across diverse composition ranges. With confidence that SRO is possible in austenitic stainless steels, we developed a discrete dislocation finite element code to understand the interaction of dislocations with SRO in the presence of H. By incorporating H effects on the dislocation emission and SRO stress field we show that the critical stress for the dislocation pileup to breakthrough the SRO domain decreases in the presence of H, which directly contributes localized deformation at the macroscale. Through the simulation of a uniaxial tension test, we demonstrated that H-induced weakening of SRO stress field and H-enhanced dislocation emission can lead to the onset of shear localization at lower macroscopic strains. As a whole, this project identified three novel alloys that show improvements in performance and cost efficiency for H-facing applications by studying correlations between alloy chemistry and deformation behavior. We also made significant advancements to experimental and computational methodologies necessary to study the chemistry and distribution of SRO across a range of alloys, which in turn allowed us to demonstrate how deformation mechanisms change due to the contributions of SRO in austenitic alloys in the presence of H. The combined advancements in fundamental understanding with novel alloy development in this project has increased the viability of next generation H-technologies for the broader public through accessible low-cost alloys and accelerated development towards future H-infrastructure.

08 HYDROGEN↗
DOE OSTI2020

Bringing Automated Fault Detection and Diagnostics Tools for HVAC&R Into the Mainstream

Heating, ventilation, and air-conditioning (HVAC) systems consume over 5 quads of energy annually, representing 30% of energy consumption in the U.S. commercial buildings. Additionally, commercial refrigeration (R) systems add about 1 quad to commercial buildings energy consumption. Most HVAC systems operate with one or more faults that result in increased energy consumption. Fault detection and diagnostics (FDD) tools have been developed to address this national issue, and many tools are commercially available. FDD tools have the potential to save considerable energy for an existing commercial rooftop unit (RTU) and refrigeration systems. These devices can be used for both retro commissioning and, when faults are addressed, continuous commissioning. However, there appears to be multiple market barriers for this technology. Although there are efforts to develop FDD tool standards, currently there are no standards and methods to define functions, capabilities, accuracy, and reliability of FDD tools in the field. Moreover, most of the commercial FDD tools have not been verified in the field independently. This paper presents a comprehensive approach for bringing HVAC FDD tools into the mainstream. The approach involves demonstrating ten commercially available FDD tools installed at ten different sites, independent testing and evaluation of the FDD tools, communication with various stakeholders, identifying and assessing market barriers, creating a process evaluation methodology, and assisting utility companies in developing incentive programs. Furthermore, the preliminary baseline results from the case study demonstrate how the use of an independent monitoring system (IMS) can be used for ground-truth in evaluating FDD tools in the field.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1992

Regional climates in the GISS global circulation model - Synoptic-scale circulation

A major weakness of current general circulation models (GCMs) is their perceived inability to predict reliably the regional consequences of a global-scale change, and it is these regional-scale predictions that are necessary for studies of human-environmental response. For large areas of the extratropics, the local climate is controlled by the synoptic-scale atmospheric circulation, and it is the purpose of this paper to evaluate the synoptic-scale circulation of the Goddard Institute for Space Studies (GISS) GCM. A methodology for validating the daily synoptic circulation using Principal Component Analysis is described, and the methodology is then applied to the GCM simulation of sea level pressure over the continental United States (excluding Alaska). The analysis demonstrates that the GISS 4 x 5 deg GCM Model II effectively simulates the synoptic-scale atmospheric circulation over the United States. The modes of variance describing the atmospheric circulation of the model are comparable to those found in the observed data, and these modes explain similar amounts of variance in their respective datasets. The temporal behavior of these circulation modes in the synoptic time frame are also comparable.

Hewitson, B.↗
NASA NTRS2018

Failure Analysis and Products in a Model-Based Environment

The work presented in this paper describes an approach, including a methodology and tools, which allows system engineers to capture failure-related information in a model and generate automatically key failure analysis products: the Failure Modes, Effects and Criticality Analysis (FMECA) and the Fault Tree Analysis (FTA). The work has been developed by Tietronix Software, Inc. and the NASA’s Jet Propulsion Laboratory (JPL), and the resulting auto-generated artifacts shown in this paper demonstrate the ability to obtain powerful reliability and fault management products in a model-based environment.

Castet, Jean-Francois↗
DOE OSTI2026

Flexible AI Models for Grid Resilience

The rapid growth in size and complexity of artificial intelligence (AI) and machine learning (ML) models has led to increased energy demands, posing a threat to the reliability of the existing power grid. This project addresses the challenge of highly intermittent and energy-intensive inference workloads by (1) developing fidelity-adaptive neural networks capable of dynamic response to grid conditions and (2) integrating these networks with power flow simulations to assess their impact on power grid reliability. We will explore both top-down and bottom-up approaches to create hierarchies of submodels that provide a controlled trade-off between power draw and prediction accuracy. The top-down method utilizes NN pruning to reduce a flagship model into progressively smaller, energy-efficient variants. The bottom-up approach employs geometrically principled weight setting strategies to construct depth-efficient models from the ground up. A real-time hardware-in-the-loop (HIL) platform will be developed to simulate a scaled AC power grid, integrating live AI workload power draw and enabling dynamic model switching in response to grid feedback. This work will provide a novel framework for evaluating the impact of flexible AI/ML workloads on grid performance and establish new methodologies for energy-aware computing in data centers. The outcomes will demonstrate that adaptive AI/ML can play a critical role in improving grid stability while advancing NREL's leadership in energy-efficient computing research.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Coordinated Integration of Renewable Generation and Small Modular Reactors in Puerto Rico – an Initial Study

With a growing interest and awareness to support clean and sustainable sources of energy, several countries have ambitious plans to significantly increase the penetration of renewable energy in the grid. However, the sources of renewable energy, such as solar and wind, are highly intermittent and therefore can pose additional challenges to maintain reliable system operations; one such challenge being flexibility requirement. This paper addresses the concerns of increasing flexibility needs with high renewable penetration, and also study the coordinated integration of nuclear small modular reactor and inverter-based renewable generation sources in a system to achieve high levels of carbon-free and sustainable energy. In this paper, balancing reserve and short-term flexibility requirements were considered for the analysis purpose. Also, methodology was developed to calculate metrics for calculating short-term flexibility requirements in the time-scale of hours. Small modular reactors are considered as potential sources of generation flexibility to complement renewables.

Agrawal, Urmila↗
DOE OSTI2020

Proper use of HHDRIFT in surveillance and production conditions

With higher quality optics, newer benchtop DRIFT (diffuse reflectance infrared Fourier transform) spectroscopy systems with modern electronic circuitries should be the preferred choice if detection sensitivity, intensity, and reliability are top priorities. However, when space consideration or other restrictions require the use of a HHDRIFT (handheld DRIFT), it is possible to convert the measurements of the HHDRIFT to those obtained from any benchtop DRIFT and vice versa. In this report, the conversion of the measurements between a HHDRIFT and a benchtop DRIFT at LLNL (Lawrence Livermore National Laboratory) are shown to be linear in both production and surveillance conditions. A similar methodology can be used to obtain the measurement correlations between any HHDRIFT and any benchtop DRIFT at other sites.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Challenges of Sustaining the International Space Station Through 2020 and Beyond: Reassessing Confidence Targets for System Availability

The International Space Station (ISS) was originally designed to operate until 2015 with a plan for deorbiting the ISS in 2016. Currently, the international partnership has agreed to extend the operations until 2020 and discussions are underway to extend the life even further to 2028. Each partner is responsible for the sustaining engineering, sparing, and maintenance of their own segments. National Aeronautics and Space Administration's (NASA's) challenge is to purchase the needed number of spares to maintain the functional availability of the ISS systems necessary for the United States On-Orbit Segment s contribution. This presentation introduces an analytical approach to assessing uncertainty in ISS hardware necessary to extend the life of the vehicle. Some key areas for consideration are: establishing what confidence targets are required to ensure science can be continuously carried out on the ISS, defining what confidence targets are reasonable to ensure vehicle survivability, considering what is required to determine if the confidence targets are too high, and whether sufficient number of spares are purchased. The results of the analysis will provide a methodological basis for reassessing vehicle subsystem confidence targets. This analysis compares the probability of existing spares exceeding the total expected unit demand of the Orbital Replacement Unit (ORU) in functional hierarchies approximating the vehicle subsystems. In cases where the functional hierarchies' availability does not meet subsystem confidence targets, the analysis will further identify which ORUs may require additional spares to extend the life of the ISS. The resulting probability is dependent upon hardware reliability estimates. However, the ISS hardware fleet carries considerable epistemic uncertainty which must be factored into the development and execution of sparing risk postures. In addition, it is also recognized that uncertainty in the assessment is due to disconnects between modeled functions and actual subsystem operations. Perhaps most importantly, it is acknowledged that conservative confidence targets per subsystem are currently accepted. This presentation will also discuss how subsystem confidence targets may be relaxed based on calculating the level of uncertainty for each corresponding ORU-function. The presentation will conclude with the various strengths and limitations for implementing the analytical approach in sustaining the ISS through end of life; 2020 and beyond.

Lutomski, Michael G.↗
NASA NTRS2019

Solar Activity Modeling: From Subgranular Dynamical Scales to the Solar Cycles

Dynamical effects of solar magnetoconvection span a wide range spatial and temporal scales that extends from the interior to the corona and from fast turbulent motions to the global-Sun magnetic activity. To study the solar activity on short temporal scales (from minutes to hours), we use 3D radiative MHD simulations that allow us to investigate complex turbulent interactions that drive various phenomena, such as plasma eruptions, spontaneous formation of magnetic structures, funnel-like structures and magnetic loops in the corona, and others. In particular, we focus on multi-scale processes of energy exchange across the different layers, which contribute to the corona heating and eruptive dynamics, as well as interlinks between different layers of the solar interior and atmosphere. For modeling the global-scale activity we use the data assimilation approach that has demonstrated great potential for building reliable long-term forecasts of solar activity. In particular, it has been shown that the Ensemble Kalman Filter (EnKF) method applied to the Parker-Kleeorin-Ruzmakin dynamo model is capable of predicting solar activity up to one sunspot cycle ahead in time, as well as estimating the properties of the next cycle a few years before it begins. In this presentation, using the available magnetogram data, we discuss development of the methodology and forecast quality criteria (including forecast uncertainties and sources of errors). We demonstrate the influence of observational limitation on the prediction accuracy. We present the EnKF predictions of the upcoming Solar Cycle 25 based on both the sunspot number series and observed magnetic fields, and discuss the uncertainties and potential of the data assimilation approach for modeling and forecasting the solar activity.

Kitiashvili, I. N.↗
NASA NTRS2019

Solar Activity Modeling: From Subgranular Dynamical Scales to the Solar Cycles

The dynamical effects of solar magnetoconvection span a wide range spatial and temporal scales that extend from the interior to the corona and from fast turbulent motions to global magnetic activity. To study the solar activity on short temporal scales (from minutes to hours), we use 3D radiative MHD simulations that allow us to investigate complex turbulent interactions that drive various phenomena, such as plasma eruptions, spontaneous formation of magnetic structures, funnel-like structures and magnetic loops in the corona, and others. In particular, we focus on multi-scale processes of energy exchange across layers of the solar interior and atmosphere, which contribute to coronal heating and eruptive dynamics. For modeling global-scale activity, we use a data assimilation approach that has demonstrated great potential for building reliable long-term forecasts of solar activity. In particular, it has been shown that the Ensemble Kalman Filter (EnKF) method applied to the Parker-Kleeorin-Ruzmakin dynamo model is capable of predicting solar activity up to one sunspot cycle ahead in time, as well as estimating the properties of the next cycle a few years before it begins. In this presentation, using the available magnetogram data, we discuss development of the methodology and forecast quality criteria (including forecast uncertainties and sources of errors). We demonstrate the influence of observational limitations on prediction accuracy, and we present the EnKF predictions of the upcoming Solar Cycle (25) based on both the sunspot number series and observed magnetic fields and discuss the uncertainties and potential of the data assimilation approach for modeling and forecasting solar activity.

Kitiashvili, I. N.↗
DOE OSTI2021

A Transformational Natural Gas Fueled Dynamic SOFC for Data Center in-Rack Power (Final Technical Report)

Data centers consume 250TWh or 1% of global electricity use in 2019. This electricity demand is expected to grow exponentially in the future. The current data center power supply relies on electric grids with diesel engines and batteries as backup; the latter is critically important because a sudden loss of power could erase crucial data, causing catastrophic economic loss. However, such a double protection architecture is costly, inefficient and polluting. In search for better in-rack power system, fuel-cell based generators have recently emerged as a promising alternative to diesel engines and batteries because of its potential to be more cost-effective, more efficient and less polluting. Among many types of fuel cells, solid oxide fuel cells stand out to be a front runner because of their ability to directly operate on natural gas that has an existing infrastructure. However, there are several critical challenges facing SOFC generators to meet the rigorous power requirements of data centers: high cost, poor reliability and more importantly, slow response to the datacenters’ dynamic load change. The unexpected overload conditions in data centers can cause fuel starvation; the latter can initiate microcracks in the anode structure, thus jeopardizing the lifetime of the SOFC generator. The current efforts to increase transient power capabilities of traditional SOFCs and therefore protect SOFC stacks from internal damage during transient loading, rely primarily upon mathematical algorithms. One of the challenges to these control methodologies is the physical limitations of the fuel delivery system such as slow response of mass flow controllers to fast power demand.

30 DIRECT ENERGY CONVERSION↗
NASA NTRS2004

NASA's Aeronautics Vision

Six long-term technology focus areas are: 1. Environmentally Friendly, Clean Burning Engines. Focus: Develop innovative technologies to enable intelligent turbine engines that significantly reduce harmful emissions while maintaining high performance and increasing reliability. 2. New Aircraft Energy Sources and Management. Focus: Discover new energy sources and intelligent management techniques directed towards zero emissions and enable new vehicle concepts for public mobility and new science missions. 3. Quiet Aircraft for Community Friendly Service. Focus: Develop and integrate noise reduction technology to enable unrestricted air transportation service to all communities. 4. Aerodynamic Performance for Fuel Efficiency. Focus: Improve aerodynamic efficiency,structures and materials technologies, and design tools and methodologies to reduce fuel burn and minimize environmental impact and enable new vehicle concepts and capabilities for public mobility and new science missions. 5. Aircraft Weight Reduction and Community Access. Focus: Develop ultralight smart materials and structures, aerodynamic concepts, and lightweight subsystems to increase vehicle efficiency, leading to high altitude long endurance vehicles, planetary aircraft, advanced vertical and short takeoff and landing vehicles and beyond. 6. Smart Aircraft and Autonomous Control. Focus: Enable aircraft to fly with reduced or no human intervention, to optimize flight over multiple regimes, and to provide maintenance on demand towards the goal of a feeling, seeing, sensing, sentient air vehicle.

Tenney, Darrel R.↗
DOE OSTI2020

An Improved Transmission Switching Algorithm for Managing Post-(N-1) Contingencies in Electricity Networks

In this presentation, we detail the shortcomings of existing transmission switching (TS) methodologies for preventing post-contingency loss of load in wide area electric power networks. Following that, we present a bi-level algorithm as an improvement to the state of the art. We show proof-of-concept level results that indicate computational viability, fast solutions, and the ability to pick the same best candidate as non computationally viable methods. Further, our method also minimizes load shedding after the contingency, thus enhancing the reliability and security of electricity supply. We also include a futuristic scenario of increased renewables and decreased natural gas sourced generators to show promising results. We grant permission for our presentation to be recorded and uploaded by the conference organizers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Improved naive Bayesian probability classifier in predictions of nuclear mass

Recently, novel statistical methods such as neural networks and Bayesian learning methods are implemented to describe the nuclear masses. Based on previous studies, an improved naive Bayesian probability (iNBP) classifier is proposed to study the nuclear masses by refining the results of sophisticated nuclear models. In the iNBP method, the prediction for nuclear masses is treated as a classification problem. The residuals are classified into several groups to generate prior and conditional probabilities, and the posterior probabilities are further determined by the Bayesian formula. We choose the expectation with maximum probability as the final prediction. Reliability of the iNBP method is assessed by analyzing the global optimizations and the extrapolating capabilities. Here, the iNBP method exhibits impressive improvements on global descriptions for different mass models. Moreover, the method shows robust extrapolating capabilities. Results demonstrate the iNBP method can be applied to predict the nuclear masses of unknown regions. Considering the local mass relations, the iNBP method can offer considerable fine-tuning of the mass descriptions from nuclear models. The methodology proposed in this paper can also be applied to other model-based extrapolations of nuclear observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Supply Chain Risk Management: Data Structuring

Supply chain risk management (SCRM) is an area of research that addresses both logistics concepts to maximize efficiency, reliability, and revenue as well as risk features, such as potential weak points, break points, and vulnerabilities within the supply chain. SCRM is used to find risks introduced at each node in a supply chain and how these risks can impact a company’s products, individuals, customers, and reputation. SCRM is a relatively new field, so standardized processes including data structuring are not fully documented. This paper explains the importance of a standard data structuring methodology and how it can enhance current SCRM efforts. Data ingest, structuring, and analysis are predominantly managed by humans. Automating some of the less complex steps can positively impact SCRM by allowing human analysts to focus on more strategic analyses. Types of data to be collected and structured are collected via publicly available information related to hardware, software, and corporate entities. After the data has been collected, the information is formatted in a specific manner, conforming to a schema, to allow for more effective and efficient ingest for further analysis. This paper outlines data structures used by Pacific Northwest National Laboratory for SCRM research and analysis purposes. These structures have been used for hundreds of analyses and have been successful in developing a common baseline. Data structuring is one of the first steps in data standardization, which will further mature and enhance the SCRM research area.

supply chain risk management, data structuring, re↗