SEARCH · Engineering Papers

Results for “distributed generation”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 883 records · Page 49

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Estimating the Meridional Extent of Adiabatic Mixing in the Stratosphere Using Age-Of-Air

Wave-induced adiabatic mixing in the winter midlatitudes is one of the key processes impacting stratospheric transport. Understanding its strength and structure is vital to understanding the distribution of trace gases and their modulation under a changing climate. Age-of-air is often used to understand stratospheric transport, and this study proposes refinements to the vertical age gradient theory of Linz et al. (2021), https://doi.org/10.1029/2021JD035199. The theory assumes exchange of air between a well-mixed tropics and a well-mixed extratropics, separated by a transport barrier, quantifying the adiabatic mixing flux across the interface using age-based measures. These assumptions are re-evaluated and a refined framework that includes the effects of meridional tracer gradients is established to quantify the mixing flux. This is achieved, in part, by computing a circulation streamfunction in age-potential temperature coordinates to generate a complete distribution of parcel ages being mixed in the midlatitudes. The streamfunction quantifies the “true” age of parcels mixed between the tropics and the extratropics. Applying the revised theory to an idealized and a comprehensive climate model reveals that ignoring the meridional gradients in age leads to an underestimation of the wave-driven mixing flux. Stronger, and qualitatively similar fluxes are obtained in both models, especially in the lower-to-middle stratosphere. While the meridional span of adiabatic mixing in the two models exhibits some differences, they show that the deep tropical pipe, that is, latitudes equatorward of 15° barely mix with older midlatitude air. The novel age-potential temperature circulation can be used to quantify additional aspects of stratospheric transport.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Sizing and Location Selection of Medium‐Voltage Back‐to‐Back Converters for DER‐Dominated Distribution Systems

Medium‐voltage back‐to‐back (MVB2B) converters can connect two distribution systems and quantifiably transfer power between them. This function can enable the MVB2B converter to exchange distributed energy resource (DER)‐generated power between two systems and bring significant value to enhancing distribution system DER adoption. Our previous work analysed and demonstrated the value MVB2B converter can bring to DER integration. As continuous work, this paper presents a methodology that helps address the MVB2B converter sizing and location selection problem in distribution systems with high DER penetrations. The proposed methodology aims to address three critical problems for MVB2B converter implementation in the real world: (1) which distribution systems are better to be connected, (2) what converter size is appropriate for connecting the distribution systems, and (3) where the optimal connection points are in the systems for connecting the MVB2B converter. The proposed methodology has been demonstrated by case studies that include various scenarios involving distribution systems with different dominated load types and high photovoltaic penetrations. The results demonstrate that selecting the optimal converter size based on net revenue and time of return considerations leads to a balance between maximizing energy savings and minimizing financial payback periods. Furthermore, feeder pair selection based on load profile standard deviation effectively identifies systems that derive the greatest value from MVB2B integration. Finally, an optimized connection point selection approach using a voltage load sensitivity matrix ensures minimal system impact while facilitating efficient power exchange. These findings provide practical insights for the real‐world deployment of MVB2B converters to enhance DER hosting capacity and improve grid resilience.

14 SOLAR ENERGY↗

DOE OSTI2022

Data augmentation for disruption prediction via robust surrogate models

The goal of this work is to generate large statistically representative data sets to train machine learning models for disruption prediction provided by data from few existing discharges. Such a comprehensive training database is important to achieve satisfying and reliable prediction results in artificial neural network classifiers. Here, we aim for a robust augmentation of the training database for multivariate time series data using Student t process regression. We apply Student t process regression in a state space formulation via Bayesian filtering to tackle challenges imposed by outliers and noise in the training data set and to reduce the computational complexity. Thus, the method can also be used if the time resolution is high. We use an uncorrelated model for each dimension and impose correlations afterwards via colouring transformations. We demonstrate the efficacy of our approach on plasma diagnostics data of three different disruption classes from the DIII-D tokamak. To evaluate if the distribution of the generated data is similar to the training data, we additionally perform statistical analyses using methods from time series analysis, descriptive statistics and classic machine learning clustering algorithms.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Data augmentation for disruption prediction via robust surrogate models

The goal of this work is to generate large statistically representative datasets to train machine learning models for disruption prediction provided by data from few existing discharges. Such a comprehensive training database is important to achieve satisfying and reliable prediction results in artificial neural network classifiers. Here, we aim for a robust augmentation of the training database for multivariate time series data using Student-t process regression. We apply Student-t process regression in a state space formulation via Bayesian filtering to tackle challenges imposed by outliers and noise in the training data set and to reduce the computational complexity. Thus, the method can also be used if the time resolution is high. We use an uncorrelated model for each dimension and impose correlations afterwards via coloring transformations. We demonstrate the efficacy of our approach on plasma diagnostics data of three different disruption classes from the DIII-D tokamak. To evaluate if the distribution of the generated data is similar to the training data, we additionally perform statistical analyses using methods from time series analysis, descriptive statistics, and classic machine learning clustering algorithms.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2009

Impact of Land Surface Heterogeneity on Mesoscale Atmospheric Dispersion

Prior numerical modelling studies show that atmospheric dispersion is sensitive to surface heterogeneities, but past studies do not consider the impact of a realistic distribution of surface heterogeneities on mesoscale atmospheric dispersion. While these focussed on dispersion in the convective boundary layer, the present work also considers dispersion in the nocturnal boundary layer and above. Using a Lagrangian particle dispersion model (LPDM) coupled to the Eulerian Regional Atmospheric Modeling System (RAMS), the impact of topographic, vegetation, and soil moisture heterogeneities on daytime and nighttime atmospheric dispersion is examined. In addition, the sensitivity to the use of Moderate Resolution Imaging Spectroradiometer (MODIS)-derived spatial distributions of vegetation characteristics on atmospheric dispersion is also studied. The impact of vegetation and terrain heterogeneities on atmospheric dispersion is strongly modulated by soil moisture, with the nature of dispersion switching from non-Gaussian to near- Gaussian behaviour for wetter soils (fraction of saturation soil moisture content exceeding 40%). For drier soil moisture conditions, vegetation heterogeneity produces differential heating and the formation of mesoscale circulation patterns that are primarily responsible for non-Gaussian dispersion patterns. Nighttime dispersion is very sensitive to topographic, vegetation, soil moisture, and soil type heterogeneity and is distinctly non-Gaussian for heterogeneous land-surface conditions. Sensitivity studies show that soil type and vegetation heterogeneities have the most dramatic impact on atmospheric dispersion. To provide more skillful dispersion calculations, we recommend the utilisation of satellite-derived vegetation characteristics coupled with data assimilation techniques that constrain soil-vegetation-atmosphere transfer (SVAT) models to generate realistic spatial distributions of surface energy fluxes.

Wu, Yuling↗

DOE OSTI2022

Cybersecurity Standards for Photovoltaic Operations

Solar energy plays an important role in securing a more resilient, cyber-secure electrical grid in Pennsylvania. Solar's ability to be widely "distributed" on residential and large roofs, marginal lands, and many other locations across Pennsylvania - as opposed to being centralized - offers a strong option for addressing the myriad of potential disruptions that can occur to the grid's infrastructure. And when combined with energy storage, local energy needs can be met immediately without having to wait on the delivery of an off-site fuel source. As more and more distributed solar electricity generation is brought online, researchers, technology developers, solar developers and grid operators are paying close attention to the potential for solar to enhance grid cybersecurity. Although nobody may know when, where, or how the next cyberattack will take place, there are security measures, technical solutions, and management practices that are being implemented across the industry to protect against network control issues and grid operations. Everyone participating in the solar value chain stands to gain from a coordinated, iterative approach to protect against cyber vulnerabilities and build deeper resilience into the architecture of our grid.

cybersecurity↗

NASA NTRS2008

Distributed Turboelectric Propulsion for Hybrid Wing Body Aircraft

Meeting future goals for aircraft and air traffic system performance will require new airframes with more highly integrated propulsion. Previous studies have evaluated hybrid wing body (HWB) configurations with various numbers of engines and with increasing degrees of propulsion-airframe integration. A recently published configuration with 12 small engines partially embedded in a HWB aircraft, reviewed herein, serves as the airframe baseline for the new concept aircraft that is the subject of this paper. To achieve high cruise efficiency, a high lift-to-drag ratio HWB was adopted as the baseline airframe along with boundary layer ingestion inlets and distributed thrust nozzles to fill in the wakes generated by the vehicle. The distributed powered-lift propulsion concept for the baseline vehicle used a simple, high-lift-capable internally blown flap or jet flap system with a number of small high bypass ratio turbofan engines in the airframe. In that concept, the engine flow path from the inlet to the nozzle is direct and does not involve complicated internal ducts through the airframe to redistribute the engine flow. In addition, partially embedded engines, distributed along the upper surface of the HWB airframe, provide noise reduction through airframe shielding and promote jet flow mixing with the ambient airflow. To improve performance and to reduce noise and environmental impact even further, a drastic change in the propulsion system is proposed in this paper. The new concept adopts the previous baseline cruise-efficient short take-off and landing (CESTOL) airframe but employs a number of superconducting motors to drive the distributed fans rather than using many small conventional engines. The power to drive these electric fans is generated by two remotely located gas-turbine-driven superconducting generators. This arrangement allows many small partially embedded fans while retaining the superior efficiency of large core engines, which are physically separated but connected through electric power lines to the fans. This paper presents a brief description of the earlier CESTOL vehicle concept and the newly proposed electrically driven fan concept vehicle, using the previous CESTOL vehicle as a baseline.

Kim, Hyun Dae↗

NASA NTRS2002

Deregulation Impact in Negotiating a New Electrical Contract Between NASA Glenn Research Center at Lewis Field and FirstEnergy Corp., Cleveland, Ohio, USA

The governor of the State of Ohio signed amended substitute Senate bill 3 on July 6, 1999, requiring Ohio's electric industry to change from a monopoly environment to a competitive electric environment for generation services. The start date for competitive retail generation services was set for January 1, 2001. This new deregulation law allowed all Ohioans to choose the supplier of generation service, but the transmission and distribution would remain regulated. It also required electric utilities to unbundle the three main components (generation, transmission, and distribution) and make other changes designed to produce a competitive electric generation market. While deregulation was taking shape, the NASA Glenn Research Center electrical contract with FirstEnergy Corp. of Cleveland, Ohio, was to expire on September 7, 1999. Glenn strategically evaluated and incorporated the impacts of electric deregulation in the negotiations. Glenn and FirstEnergy spent over a year in negotiations until the Glenn utility team and the FirstEnergy negotiating team came to an agreement in the fall of 2000, and a new contract became effective on January 1, 2001.

Quach, Quyen T.↗

NASA NTRS1999

Automatic Data Distribution for CFD Applications on Structured Grids

Development of HPF versions of NPB and ARC3D showed that HPF has potential to be a high level language for parallelization of CFD applications. The use of HPF requires an intimate knowledge of the applications and a detailed analysis of data affinity, data movement and data granularity. Since HPF hides data movement from the user even with this knowledge it is easy to overlook pieces of the code causing low performance of the application. In order to simplify and accelerate the task of developing HPF versions of existing CFD applications we have designed and partially implemented ADAPT (Automatic Data Distribution and Placement Tool). The ADAPT analyzes a CFD application working on a single structured grid and generates HPF TEMPLATE, (RE)DISTRIBUTION, ALIGNMENT and INDEPENDENT directives. The directives can be generated on the nest level, subroutine level, application level or inter application level. ADAPT is designed to annotate existing CFD FORTRAN application performing computations on single or multiple grids. On each grid the application can considered as a sequence of operators each applied to a set of variables defined in a particular grid domain. The operators can be classified as implicit, having data dependences, and explicit, without data dependences. In order to parallelize an explicit operator it is sufficient to create a template for the domain of the operator, align arrays used in the operator with the template, distribute the template, and declare the loops over the distributed dimensions as INDEPENDENT. In order to parallelize an implicit operator, the distribution of the operator's domain should be consistent with the operator's dependences. Any dependence between sections distributed on different processors would preclude parallelization if compiler does not have an ability to pipeline computations. If a data distribution is "orthogonal" to the dependences of an implicit operator then the loop which implements the operator can be declared as INDEPENDENT.

Frumkin, Michael↗

NASA NTRS2011

NASA Tech Briefs, December 2011

Topics covered include: 1) SNE Industrial Fieldbus Interface; 2) Composite Thermal Switch; 3) XMOS XC-2 Development Board for Mechanical Control and Data Collection; 4) Receiver Gain Modulation Circuit; 5) NEXUS Scalable and Distributed Next-Generation Avionics Bus for Space Missions; 6) Digital Interface Board to Control Phase and Amplitude of Four Channels; 7) CoNNeCT Baseband Processor Module; 8) Cryogenic 160-GHz MMIC Heterodyne Receiver Module; 9) Ka-Band, Multi-Gigabit-Per-Second Transceiver; 10) All-Solid-State 2.45-to-2.78-THz Source; 11) Onboard Interferometric SAR Processor for the Ka-Band Radar Interferometer (KaRIn); 12) Space Environments Testbed; 13) High-Performance 3D Articulated Robot Display; 14) Athena; 15) In Situ Surface Characterization; 16) Ndarts; 17) Cryo-Etched Black Silicon for Use as Optical Black; 18) Advanced CO2 Removal and Reduction System; 19) Correcting Thermal Deformations in an Active Composite Reflector; 20) Umbilical Deployment Device; 21) Space Mirror Alignment System; 22) Thermionic Power Cell To Harness Heat Energies for Geothermal Applications; 23) Graph Theory Roots of Spatial Operators for Kinematics and Dynamics; 24) Spacesuit Soft Upper Torso Sizing Systems; 25) Radiation Protection Using Single-Wall Carbon Nanotube Derivatives; 26) PMA-PhyloChip DNA Microarray to Elucidate Viable Microbial Community Structure; 27) Lidar Luminance Quantizer; 28) Distributed Capacitive Sensor for Sample Mass Measurement; 29) Base Flow Model Validation; 30) Minimum Landing Error Powered-Descent Guidance for Planetary Missions; 31) Framework for Integrating Science Data Processing Algorithms Into Process Control Systems; 32) Time Synchronization and Distribution Mechanisms for Space Networks; 33) Local Estimators for Spacecraft Formation Flying; 34) Software-Defined Radio for Space-to-Space Communications; 35) Reflective Occultation Mask for Evaluation of Occulter Designs for Planet Finding; and 36) Molecular Adsorber Coating

Source record↗

DOE OSTI2025

Comparing three generations of D-Wave quantum annealers for minor embedded combinatorial optimization problems

Abstract Quantum annealing (QA) is a novel type of analog computation that aims to use quantum mechanical fluctuations to search for optimal solutions of Ising problems. QA in the transverse Ising model, implemented on D-Wave quantum processing units, are available as cloud computing resources. In this study we report concise benchmarks across three generations of D-Wave quantum annealers, consisting of four different devices, for the NP-hard discrete combinatorial optimization problems unweighted maximum clique and unweighted maximum cut on random graphs. The Ising, or equivalently quadratic unconstrained binary optimization, formulation of these problems do not require auxiliary variables for order reduction, and their overall structure and weights are not highly variable, which makes these problems simple test cases to understand the sampling capability of current D-Wave quantum annealers. All-to-all minor embeddings of size 52, with relatively uniform chain lengths, are used for a direct comparison across the Chimera, Pegasus, and Zephyr device topologies. A grid-search over annealing times and the minor embedding chain strengths is performed in order to determine the level of reasonable performance for each device and problem type. Experiment metrics that are reported are approximation ratios for non-broken chain samples, chain break proportions, and time-to-solution for the maximum clique problem instances. How fairly the quantum annealers sample optimal maximum cliques, for instances which contain multiple maximum cliques, is quantified using entropy of the measured ground state distributions. The newest generation of quantum annealing hardware, which has a Zephyr hardware connectivity, performed the best overall with respect to approximation ratios and chain break frequencies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2015

Initial Operation of the Nuclear Thermal Rocket Element Environmental Simulator

The Nuclear Thermal Rocket Element Environmental Simulator (NTREES) facility is designed to perform realistic non-nuclear testing of nuclear thermal rocket (NTR) fuel elements and fuel materials. Although the NTREES facility cannot mimic the neutron and gamma environment of an operating NTR, it can simulate the thermal hydraulic environment within an NTR fuel element to provide critical information on material performance and compatibility. The NTREES facility has recently been upgraded such that the power capabilities of the facility have been increased significantly. At its present 1.2 MW power level, more prototypical fuel element temperatures nay now be reached. The new 1.2 MW induction heater consists of three physical units consisting of a transformer, rectifier, and inverter. This multiunit arrangement facilitated increasing the flexibility of the induction heater by more easily allowing variable frequency operation. Frequency ranges between 20 and 60 kHz can accommodated in the new induction heater allowing more representative power distributions to be generated within the test elements. The water cooling system was also upgraded to so as to be capable of removing 100% of the heat generated during testing In this new higher power configuration, NTREES will be capable of testing fuel elements and fuel materials at near-prototypic power densities. As checkout testing progressed and as higher power levels were achieved, several design deficiencies were discovered and fixed. Most of these design deficiencies were related to stray RF energy causing various components to encounter unexpected heating. Copper shielding around these components largely eliminated these problems. Other problems encountered involved unexpected movement in the coil due to electromagnetic forces and electrical arcing between the coil and a dummy test article. The coil movement and arcing which were encountered during the checkout testing effectively destroyed the induction coil in use at the time and resulted in NTREES being out of commission for a couple of months while a new stronger coil was procured. The new coil includes several additional pieces of support structure to prevent coil movement in the future. In addition, new insulating test article support components have been fabricated to prevent unexpected arcing to the test articles. Additional activities are also now underway to address ways in which the radial temperature profiles across test articles may be controlled such that they are more prototypical of what they would encounter in an operating nuclear engine. The causes of the temperature distribution problem are twofold. First, the fuel element test article is isolated in NTREES as opposed to being in the midst of many other mostly identical fuel elements in a nuclear engine. As a result, the fuel element heat flux boundary conditions in NTREES are far from adiabatic as would normally be the case in a reactor. Second, induction heating skews the power distribution such that power is preferentially deposited near the outside of the fuel element. Nuclear heating, conversely, deposits its power much more uniformly throughout the fuel element. Current studies are now looking at various schemes to adjust the amount of thermal radiation emitted from the fuel element surface so as to essentially vary the thermal boundary conditions on the test article. It is hoped that by properly adjusting the thermal boundary conditions on the fuel element test article, it may be possible to substantially correct for the inappropriate radial power distributions resulting from the induction heating so as to yield a more nearly correct temperature distribution throughout the fuel element.

Emrich, William J., Jr.↗

NASA NTRS2014

Nuclear Thermal Rocket Element Environmental Simulator (NTREES) Upgrade Activities

Over the past year the Nuclear Thermal Rocket Element Environmental Simulator (NTREES) has been undergoing a significant upgrade beyond its initial configuration. The NTREES facility is designed to perform realistic non-nuclear testing of nuclear thermal rocket (NTR) fuel elements and fuel materials. Although the NTREES facility cannot mimic the neutron and gamma environment of an operating NTR, it can simulate the thermal hydraulic environment within an NTR fuel element to provide critical information on material performance and compatibility. The first phase of the upgrade activities which was completed in 2012 in part consisted of an extensive modification to the hydrogen system to permit computer controlled operations outside the building through the use of pneumatically operated variable position valves. This setup also allows the hydrogen flow rate to be increased to over 200 g/sec and reduced the operation complexity of the system. The second stage of modifications to NTREES which has just been completed expands the capabilities of the facility significantly. In particular, the previous 50 kW induction power supply has been replaced with a 1.2 MW unit which should allow more prototypical fuel element temperatures to be reached. The water cooling system was also upgraded to so as to be capable of removing 100% of the heat generated during. This new setup required that the NTREES vessel be raised onto a platform along with most of its associated gas and vent lines. In this arrangement, the induction heater and water systems are now located underneath the platform. In this new configuration, the 1.2 MW NTREES induction heater will be capable of testing fuel elements and fuel materials in flowing hydrogen at pressures up to 1000 psi at temperatures up to and beyond 3000 K and at near-prototypic reactor channel power densities. NTREES is also capable of testing potential fuel elements with a variety of propellants, including hydrogen with additives to inhibit corrosion of certain potential NTR fuel forms. Additional diagnostic upgrades included in the present NTREES set up include the addition of a gamma ray spectrometer located near the vent filter to detect uranium fuel particles exiting the fuel element in the propellant exhaust stream to provide additional information any material loss occurring during testing. Other aspects of the upgrade included reworking NTREES to reduce the operational complexity of the system despite the increased complexity of the induction heating system. To this end, many of the controls were consolidated on fewer panels. As part of this upgrade activity, the Safety Assessment (SA) and the Standard Operating Procedures (SOPs) for NTREES were extensively rewritten. The new 1.2 MW induction heater consists of three physical units consisting of a transformer, rectifier, and inverter. This multiunit arrangement facilitated increasing the flexibility of the induction heater by more easily allowing variable frequency operation. Frequency ranges between 20 and 60 kHz can be accommodated in the new induction heater allowing more representative power distributions to be generated within the test elements.

Emrich, William J., Jr.↗

NASA NTRSDate not supplied

Assessment of Crew Time for Maintenance and Repairs Activities for Lunar Surface Missions

NASA is currently evaluating different methods to predict how much time crewmembers will spend conducting repair and maintenance activities on future space missions. As mission scope and spacecraft architectures change, it will be necessary to understand how crew repair and maintenance timelines are impacted by mission operations and technology changes. Past work has been done using historical ISS data to accurately predict crew habitation and operation timelines, resulting in the development of NASA’s Exploration Crew Time Model (ECTM). However, understanding crew maintenance and repair requirements has posed a unique challenge due to the complexity of available datasets, the probabilistic nature of sub-system failures, and the impacts of reliability growth on failure rates. This paper presents a methodology to collect and condition empirical repair and maintenance time data from available data sets, to extrapolate from that data to estimate projected maintenance and repair times for a lunar Surface Habitat, and to assess how uncertainty in repair time could impact utilization time on the lunar surface. NASA International Space Station (ISS) maintenance and crew time data are logged into two central databases, the Maintenance Data Collection (MDC) and the Operations Planning Timeline Integration System (OPTimIS) respectively. Separately, each of these two datasets capture only portions of the complete set of data required to generate an accurate assessment of crew time spent on maintenance activities at a sub-system level. MDC provides a detailed catalog of failure events and an overview of the failure’s required maintenance and OPTimIS provides a description of crew activities and crew time durations dedicated to maintenance. To create a more useful crew time estimate for maintenance timelines, the authors developed a methodology to capture relevant data from each set and combine and utilize that data by linking crew time requirements to specific components. The authors compare the failure logs in the MDC to crew activity logs pulled from OPTimIS and then process the data to estimate required repair times for each failure event. Data is also classified by the outcome of each repair event, whether the failed component was replaced or whether it was repaired in place. The entire maintenance activity dataset is then categorized based on the class of failed component to allow for a statistically significant sample size for each class and to provide accurate crew time estimates for any components lacking relevant data. This resultant component repair time data can be used in the future to generate Mean Time To Repair (MTTR) estimates and confidence intervals for each class of component based on a probabilistic distribution of documented maintenance events. These improved MTTR values can then be applied to candidate element sub-system architectures, along with component Mean Time Between Failure (MTBF) data to generate distributions for potential required system crew repair time estimates for a given mission. Repair time distributions can then be used to develop more accurate crew schedules and to assess potential available utilization time.

Crew Time↗

NASA NTRSDate not supplied

Assessment of Crew Time for Maintenance and Repair Activities for Lunar Surface Missions

NASA is currently evaluating different methods to predict how much time crewmembers will spend conducting repair and maintenance activities on future space missions. As mission scope and spacecraft architectures change, understanding how crew repair and maintenance timelines are impacted by mission operations and technology changes is vital for future mission planning. Past work has been done using historical International Space Station (ISS) data to accurately predict crew habitation and operation timelines, resulting in the development of NASA’s Exploration Crew Time Model (ECTM). However, understanding crew maintenance and repair requirements has posed a unique challenge due to the complexity of available datasets, the probabilistic nature of sub-system failures, and the impacts of reliability growth on failure rates. This paper presents a methodology to collect and condition empirical repair and maintenance time data from available datasets, to extrapolate from that data to estimate projected maintenance and repair times for a lunar Surface Habitat (SH), and to assess how uncertainty in repair time could impact utilization time on the lunar surface. NASA ISS maintenance and crew time data are logged into two central databases: the Maintenance Data Collection (MDC) and the Operations Planning Timeline Integration System (OPTimIS). Separately, each of these two datasets capture only portions of the complete set of data required to generate an accurate assessment of crew time spent on maintenance activities at a sub-system level. To create a more useful crew time estimate for maintenance timelines, the authors developed a methodology to capture relevant data from each set and combine and utilize that data by linking crew time requirements to specific components. The authors compare the failure logs in the MDC to crew activity logs pulled from OPTimIS and then process the data to estimate required repair time for each failure and repair event. The entire maintenance activity dataset is then categorized based on the class of failed component to ensure a significant sample size for each class and accurate crew time estimates for any components lacking relevant data. This resultant component repair time data can be used in the future to generate Mean Time to Repair (MTTR) estimates and confidence intervals for each class of component based on a probabilistic distribution of documented maintenance events. These improved MTTR values can then be applied to candidate element sub-system architectures, along with component Mean Time Between Failure (MTBF) data to generate distributions for potential required system crew repair time estimates for a given mission. The authors applied these modeling methods to a case study of a crewed mission to the planned SH and produced expected corrective maintenance crew time distributions. The results produced an expected corrective maintenance crew time at over 24 hours per mission, and a maintenance crew time distribution that reflects the importance of planning for sufficient maintenance requirements each mission. Repair time distributions can then be used to develop more accurate crew schedules and to assess potential available utilization time.

Crew Time↗

NASA NTRS1998

Three-Dimensional Measurements of Fuel Distribution in High-Pressure, High- Temperature, Next-Generation Aviation Gas Turbine Combustors

In our world-class, optically accessible combustion facility at the NASA Lewis Research Center, we have developed the unique capability of making three-dimensional fuel distribution measurements of aviation gas turbine fuel injectors at actual operating conditions. These measurements are made in situ at the actual operating temperatures and pressures using the JP-grade fuels of candidate next-generation advanced aircraft engines for the High Speed Research (HSR) and Advanced Subsonics Technology (AST) programs. The inlet temperature and pressure ranges used thus far are 300 to 1100 F and 80 to 250 psia. With these data, we can obtain the injector spray angles, the fuel mass distributions of liquid and vapor, the degree of fuel vaporization, and the degree to which fuel has been consumed. The data have been used to diagnose the performance of injectors designed both in-house and by major U.S. engine manufacturers and to design new fuel injectors with overall engine performance goals of increased efficiency and reduced environmental impact. Mie scattering is used to visualize the liquid fuel, and laser-induced fluorescence is used to visualize both liquid and fuel vapor.

Hicks, Yolanda R.↗

DOE OSTI2020

Real-Time Distributed Control of Smart Inverters for Network-level Optimization

The limitations of centralized optimization methods in managing electric power distribution systems operations have led to the distributed paradigm of computing and decision-making. Unfortunately, the existing distributed optimization algorithms are limited in their applicability to managing fast varying phenomena such as those resulting from highly variable Distributed Energy Resource (DER) generation patterns. They require a large number of communication rounds (in the order of 10 2 to 10 3 ) among the computing agents to solve one instance of the optimization problem. Related real-time distributed control methods are equally limited in their applications to power distribution systems with fast-changing DER generation; they require hundreds of rounds of communication and thus are slow in tracking the network-level optimal solutions. In this paper, we propose a novel distributed voltage controller that provides a fast-tracking of rapidly varying DER generation profiles while simultaneously converging to network-level optimal solutions within a few communication rounds. The proposed control algorithm leverages the radial topology of the system, which reduces the required communication rounds to reach the network-level optimum solution by order of magnitude. The novelty lies in carefully reducing the electrical network model from the perspective of each distributed controller and enabling appropriate data sharing among upstream and downstream nodes to achieve fast convergence. The simulation results demonstrate the effectiveness of the proposed approach in minimizing the feeder losses while maintaining the node voltage within the pre-specified limits.

voltage control, optimization, reactive power, inv↗

DOE OSTI2022

Quantifying the impact of temporal analysis of products reactor initial state uncertainties on kinetic parameters

The temporal analysis of products (TAP) reactor, a transient kinetic tool, provides users with information as the catalyst state evolves. However, the state of the art for TAP uncertainty quantification only considers the experimental noise present in the outlet flow signal. Additional sources of uncertainty, including, but not limited to, initial surface coverages, the catalyst zone location, the inert void fraction, and the gas pulse intensity and pulse delay, are not included. For this reason, a framework for quantifying all uncertainty sources present in TAP experiments is presented and applied to a carbon monoxide oxidation case study. Herein, two methods for quantifying these sources of uncertainty are introduced. The first utilizes initial state sensitivities to approximate the parameter variances, as well as to provide insights into the structural certainty of the model. The second generates parameter confidence distributions through an ensemble-based sampling algorithm. This initial state covariance matrix can ultimately be merged with the experimental noise covariance matrix, providing a unified description of the parameter uncertainties for a single TAP experiment.

36 MATERIALS SCIENCE↗