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At least 433 records · Page 24

Stirling Convertor Fasteners Reliability Quantification

Onboard Radioisotope Power Systems (RPS) being developed for NASA s deep-space science and exploration missions require reliable operation for up to 14 years and beyond. Stirling power conversion is a candidate for use in an RPS because it offers a multifold increase in the conversion efficiency of heat to electric power and reduced inventory of radioactive material. Structural fasteners are responsible to maintain structural integrity of the Stirling power convertor, which is critical to ensure reliable performance during the entire mission. Design of fasteners involve variables related to the fabrication, manufacturing, behavior of fasteners and joining parts material, structural geometry of the joining components, size and spacing of fasteners, mission loads, boundary conditions, etc. These variables have inherent uncertainties, which need to be accounted for in the reliability assessment. This paper describes these uncertainties along with a methodology to quantify the reliability, and provides results of the analysis in terms of quantified reliability and sensitivity of Stirling power conversion reliability to the design variables. Quantification of the reliability includes both structural and functional aspects of the joining components. Based on the results, the paper also describes guidelines to improve the reliability and verification testing.

Shah, Ashwin R.↗

Load Control for Frequency Response - A Literature Review

As electricity grids employ greater fractions of renewable energy, which introduce additional variability and uncertainty in the net load, balancing electrical load and generation becomes more challenging. This paper reviews the literature documenting physical simulations and real systems that employ load control (LC) for frequency response and other grid services, which balance net load on the grid and prevent unwanted frequency excursions. Apart from academic and simulation studies, few sources exist on large-scale laboratory hardware testing or actual real-world systems that employ LC for frequency response, and we review them here. Four types of systems that we consider are: 1) Laboratory-based LC experiments, 2) Isolated microgrids that employ LC, 3) Larger grids that employ LC and 4) vehicle-to-grid (V2G) technology, using electric vehicles (EVs). In general, these systems have successfully used LC to meet their objectives, which are often keeping grid frequency within a required band. However, LC struggled to balance grid frequency in an isolated system powered by a single wind turbine, and V2G technology requires refinement in communication and control to provide optimal regulation that adheres to industry standards. As LC grows in the energy industry, we have three main recommendations: 1) encouraging system operators who use LC to publish system characteristics and lessons learned; 2) transitioning more LC theoretical/simulated systems to physical experiments, and physical experiments to real-world pilot systems; 3) demonstrating load control to support isolated, high-wind-contribution systems.

17 WIND ENERGY↗

Initial testing of a variable-stroke Stirling engine

In support of the U.S. Department of Energy's Stirling Engine Highway Vehicle Systems Program, NASA Lewis Research Center is evaluating variable-stroke control for Stirling engines. The engine being tested is the Advenco Stirling engine; this engine was manufactured by Philips Research Laboratories of the Netherlands and uses a variable-angle swash-plate drive to achieve variable stroke operation. The engine is described, initial steady-state test data taken at Lewis are presented, a major drive system failure and subsequent modifications are described. Computer simulation results are presented to show potential part-load efficiency gains with variable-stroke control.

Thieme, L. G.↗

A 4-D Climatology (1979-2009) of the Monthly Tropospheric Aerosol Optical Depth Distribution over the Mediterranean Region from a Comparative Evaluation and Blending of Remote Sensing and Model Products

Since the 1980s several spaceborne sensors have been used to retrieve the aerosol optical depth (AOD) over the Mediterranean region. In parallel, AOD climatologies coming from different numerical model simulations are now also available, permitting to distinguish the contribution of several aerosol types to the total AOD. In this work, we perform a comparative analysis of this unique multiyear database in terms of total AOD and of its apportionment by the five main aerosol types (soil dust, seasalt, sulfate, black and organic carbon). We use 9 different satellite-derived monthly AOD products: NOAA/AVHRR, SeaWiFS (2 products), TERRA/MISR, TERRA/MODIS, AQUA/MODIS, ENVISAT/MERIS, PARASOL/POLDER and MSG/SEVIRI, as well as 3 more historical datasets: NIMBUS7/CZCS, TOMS (onboard NIMBUS7 and Earth- Probe) and METEOSAT/MVIRI. Monthly model datasets include the aerosol climatology from Tegen et al. (1997), the climate-chemistry models LMDz-OR-INCA and RegCM-4, the multi-model mean coming from the ACCMIP exercise, and the reanalyses GEMS and MACC. Ground-based Level- 2 AERONET AOD observations from 47 stations around the basin are used here to evaluate the model and satellite data. The sensor MODIS (on AQUA and TERRA) has the best average AOD scores over this region, showing a relevant spatio-temporal variability and highlighting high dust loads over Northern Africa and the sea (spring and summer), and sulfate aerosols over continental Europe (summer). The comparison also shows limitations of certain datasets (especially MERIS and SeaWiFS standard products). Models reproduce the main patterns of the AOD variability over the basin. The MACC reanalysis is the closest to AERONET data, but appears to underestimate dust over Northern Africa, where RegCM-4 is found closer to MODIS thanks to its interactive scheme for dust emissions. The vertical dimension is also investigated using the CALIOP instrument. This study confirms differences of vertical distribution between dust aerosols showing a large vertical spread, and other continental and marine aerosols which are confined in the boundary layer. From this compilation, we propose a 4-D blended product from model and satellite data, consisting in monthly time series of 3-D aerosol distribution at a 50 km horizontal resolution over the Euro-Mediterranean marine and continental region for the 2003-2009 period. The product is based on the total AOD from AQUA/MODIS, apportioned into sulfates, black and organic carbon from the MACC reanalysis, and into dust and sea-salt aerosols from RegCM-4 simulations, which are distributed vertically based on CALIOP climatology.We extend the 2003-2009 reconstruction to the past up to 1979 using the 2003-2009 average and applying the decreasing trend in sulfate aerosols from LMDz-OR-INCA, whose AOD trends over Europe and the Mediterranean are median among the ACCMIP models. Finally optical properties of the different aerosol types in this region are proposed from Mie calculations so that this reconstruction can be included in regional climate models for aerosol radiative forcing and aerosol-climate studies.

troposphere↗

Cell design and manufacturing changes during the past decade

Eight of the most important changes that occurred in the GE 12 AH cell over the past ten years, which are currently being used are evaluated, and a systematic approach to compare their relative merits is presented. Typical positive thickness, typical negative thickness, positive loading, negative loading, final KOH quantity, and precharge as adjustment are shown for the control cell, and the following variables: Teflon treatment; silver treatment; light loading; no PQ treatment; polypropylene separator; the A.K. 1968 plate design no PQ, old elec process, no decarb process and the A.K. 1968 plate design, no PQ, present aerospace processes. The acceptance test cell voltage and cell pressure performance and capacity test results are included.

Baer, D. A.↗

Reliability-Based Damage Tolerance Framework for Achieving Highly Reusable Launch Systems

The United States Space Force and NASA are exploring approaches that enable rapid launch response via highly reusable launch systems. One hindrance to achieving high reusability is the inability to meet damage tolerance requirements. To this end, a framework for applying reliability-based damage tolerance to space structures is presented. The reliability-based approach employs probabilistic distributions of key input variables such as material properties, geometry, loads, inspection probability, and defect characteristics to predict hardware reliability for the planned mission life. The probabilistic variables needed to perform the reliability assessments are defined and recommendations on how to collect the required data are provided. Several example problems illustrate the implementation and execution of this approach.

Leland Shimizu↗

Estimating the cost of mental loading in a bimodal divided-attention task: Combining reaction time, heart-rate variability and signal-detection theory

Multiple approaches are necessary for understanding and measuring workload. In particular, physiological systems identifiable by employing cardiac measures are related to cognitive systems. One issue of debate in measuring cardiac output is the grain of analysis used in recording and summarizing data. Various experiments are reviewed, the majority of which were directed at supporting or contradicting Lacey's intake-rejection hypothesis. Two of the experiments observed heart rate in operational environments and found virtually no changes associated with mental load. The major problems facing researchers using heart rate variability, or sinus arrhthmia, as a dependent measure have been associated with valid and sensitive scoring and preventing contamination of observed results by influences unrelated to cognition. Spectral analysis of heart rate variability offers two useful procedures: analysis from the time domain and analysis from the frequency domain. Most recently, data have been collected in a divided attention experiment, the performance measures and cardiac measures of which are detailed.

Casper, Patricia A.↗

Assessing the performance of global thermostat adjustment in commercial buildings for load shifting demand response

Abstract Efficiently leveraging new sources of flexibility is critical to mitigating load balancing challenges posed by variable renewable resources. The thermal inertia of commercial buildings allows us to shift their power consumption on minute to hourly timescales to provide demand response to the grid while maintaining occupant comfort. Global thermostat adjustment (GTA) provides a readily available and scalable approach for implementing load shifting demand response using commercial heating, ventilation, and air conditioning (HVAC) systems, since it leverages the inherent sophistication of modern building automation systems. However, there is an incomplete understanding of GTA’s performance for this purpose and its impact on building systems and occupant comfort. In this paper, we explore the performance of GTA by analyzing results from nearly nine hundred experiments on eight university campus buildings in Michigan and North Carolina. Using GTA, we manipulate each building’s thermostat setpoints causing the building to shift its power consumption with respect to its baseline. We quantify the magnitude of HVAC power response, energy use of HVAC subsystems, and impact on occupant comfort. Finally, we connect our experimental results with power system operation using an optimization model that coordinates GTA actions across a large collection of grid-interactive efficient buildings (GEBs) to reduce high ramp rates on the grid and mitigate renewable energy curtailment. Overall, our work finds that the impacts on HVAC subsystems are often complex, and may result in additional energy being consumed by fans and terminal reheat. These effects must be considered when using GTA for load shifting. Additionally, we demonstrate that occupant comfort, as assessed by indoor temperature and humidity, can be maintained during GTA events. From a societal perspective, our modeling work finds that the additional renewable energy that can be integrated through the use of GTA strategies eclipses any additional energy consumed by buildings.

Keskar, Aditya (ORCID:0000000244617980)↗

Probabilistic structural analysis of space propulsion system turbine blades

Probabilistic loads and stress analysis methods are presently applied to the second-stage blade of the SSME's high-pressure fuel turbopump, in order to illustrate how loads and stress responses can be quantified probabilistically and how the sensitivity of such component- and engine-level independent variables as engine inlet temperatures and local seal wear within the turbopump can be determined. Attention is given to a method for the derivation of probabilistic pressure, temperature, and centrifugal steady-state load descriptions of this second-stage blade from the top of the airfoil to its intersection with the firtree. Dependent-load random variables are obtained from a multilevel physical model in which duty cycle-dependent deterministic loads and related probabilistic variations are accounted for.

Newell, J. F.↗

Testing of a variable-stroke Stirling engine

Testing of a variable-stroke Stirling engine at NASA Lewis has been completed. In support of the DOE Stirling Engine Highway Vehicle Systems Program, the engine was tested for about 70 hours total with both He and H2 working fluids over a range of pressures and strokes. A direct comparison was made of part-load efficiencies obtained with variable-stroke (VS) and variable-pressure operation. Two failures with the variable-angle swash-plate drive system limited testing to low power levels. These failures are not thought to be caused by problems inherent with the VS concept but do emphasize the need for careful design in the area of the crossheads.

Thieme, L. G.↗

Testing of a variable-stroke Stirling engine

Testing of a variable-stroke Stirling engine at NASA Lewis has been completed. In support of the DOE Stirling Engine Highway Vehicle Systems Program, the engine was tested for about 70 hours total with both He and H2 as working fluids over a range of pressures and strokes. A direct comparison was made of part-load efficiencies obtained with variable-stroke (VS) and variable-pressure operation. Two failures with the variable-angle swash-plate drive system limited testing to low power levels. These failures are not thought to be caused by problems inherent with the VS concept but do emphasize the need for careful design in the area of the crossheads.

Thieme, Lanny G.↗

Design of a Distributed Propulsion Concept Using an Adjoint-Based Approach and Blade Element Theory to Minimize Power

The adjoint-based design capability in FUN3D is extended to allow efficient gradient-based optimization and design of concepts with highly integrated and distributed aero-propulsive systems. Previous work by the authors demonstrated the derivation and application of design sensitivities of flow power and vehicle forces with respect to design variables associated with actuator disk size, loading, and installation on the aircraft. In this work, calculations of propulsive power, shaft power, and propeller efficiency using blade element-based disk loading, along with sensitivity derivatives needed to perform adjoint-based design, have been implemented. This includes the derivation of additional design sensitivities for actuator disk variables with respect to the radial distributions of blade pitch angle and chord length. The blade element-based loading implementation allows us to tailor the actuator disk loading to provide greater design authority and calculate the torque imparted on the flow for the modeling of swirl effects. The design capability is demonstrated by the optimization of NASA's parallel hybrid electric PEGASUS aircraft concept. The optimization objective is the minimization of shaft power at the aerodynamic interface planes for the wing-mounted and tail-cone boundary layer ingestion propulsors, subject to vehicle performance and propulsive constraints.

Irian Ordaz↗

Load Matching Potential of Urban Renewables during Extreme Heat in New York City

Integration of renewable resources to meet growing energy demand is becoming a global priority under decarbonization mandates. This study contributes to ongoing efforts on the matter by assessing the feasibility of using offshore wind and rooftop photovoltaic systems to meet electricity demand during a period of thermal stress in New York City—August 2019. A unified modelling framework, based on the Urbanized Weather Research and Forecasting model, is used to simulate climate, renewable resources and energy demand variables. Findings show significant energy load miss-match, ranging from 3 to 5 GW, between the demand and the composite renewable generation outcome. This study provides a transferable framework for evaluating renewable integration in dense urban regions and highlights the need for additional strategies to support grid resilience during extreme heat events, while clarifying the role of local resources in fully managing NYC’s load.

54 ENVIRONMENTAL SCIENCES↗

Learning-Accelerated ADMM for Distributed DC Optimal Power Flow

We suggest a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions. Using previous observations of ADMM trajectories for a given system under varying load, the method trains a recurrent neural network (RNN) to predict the converged values of dual and consensus variables. Given a new realization of system load, a small number of initial ADMM iterations is taken as input to infer the converged values and directly inject them into the iteration. We empirically demonstrate that the online injection of these values into the ADMM iteration accelerates convergence by a significant factor for partitioned 14-, 118-and 2848-bus test systems under differing load scenarios. The proposed method has several advantages: it maintains the security of private decision variables inherent in consensus ADMM; inference is fast and so may be used in online settings; RNN-generated predictions can dramatically improve time to convergence but, by construction, can never result in infeasible ADMM subproblems; it can be easily integrated into existing software implementations. While we focus on the ADMM formulation of distributed DC-OPF in this paper, the ideas presented are naturally extended to other distributed optimization problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Learning-Accelerated ADMM for Distributed DC Optimal Power Flow

We propose a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions. Using previous observations of ADMM trajectories for a given system under varying load, the method trains a recurrent neural network (RNN) to predict the converged values of dual and consensus variables. Given a new realization of system load, a small number of initial ADMM iterations is taken as input to infer the converged values and directly inject them into the iteration. We empirically demonstrate that the online injection of these values into the ADMM iteration accelerates convergence by a significant factor for partitioned 14-, 118- and 2848-bus test systems under differing load scenarios. The proposed method has several advantages: it maintains the security of private decision variables inherent in consensus ADMM; inference is fast and so may be used in online settings; RNN-generated predictions can dramatically improve time to convergence but, by construction, can never result in infeasible ADMM subproblems; it can be easily integrated into existing software implementations. While we focus on the ADMM formulation of distributed DC-OPF in this paper, the ideas presented are naturally extended to other distributed optimization problems.

alternating direction method of multipliers↗

Thermoviscoplastic model with application to copper

A viscoplastic model is developed which is applicable to anisothermal, cyclic, and multiaxial loading conditions. Three internal state variables are used in the model; one to account for kinematic effects, and the other two to account for isotropic effects. One of the isotropic variables is a measure of yield strength, while the other is a measure of limit strength. Each internal state variable evolves through a process of competition between strain hardening and recovery. There is no explicit coupling between dynamic and thermal recovery in any evolutionary equation, which is a useful simplification in the development of the model. The thermodynamic condition of intrinsic dissipation constrains the thermal recovery function of the model. Application of the model is made to copper, and cyclic experiments under isothermal, thermomechanical, and nonproportional loading conditions are considered. Correlations and predictions of the model are representative of observed material behavior.

Freed, Alan D.↗

Unified Modeling Architecture for Load Management in Extreme Heat: The New York City Case

Integration of renewable resources to meet growing energy demand is becoming a global priority under decarbonization mandates. This study contributes to ongoing efforts on this key subject by assessing the feasibility of using coastal-urban renewable energy resources, namely, offshore wind and rooftop photovoltaic systems, to meet electricity demand of New York City during the intense recent heat wave period of June 2025. A unified modeling framework, based on the urbanized weather research and forecasting model, is used to simulate climate, renewable resources, and energy demand variables. Findings show significant energy load mismatch of approximately 1150 GWh over the month, between the demand and the combined renewable generation outcome. Three storage integration scenarios are analyzed to mitigate the deficits, reducing said deficits by a minimum of approximately 9% over the duration of the month. This study provides a transferable modeling framework tool for evaluating renewable integration in dense urban environments that can be used by grid operators to support grid resilience during extreme heat events.

54 ENVIRONMENTAL SCIENCES↗

Using probabilistic solar power forecasts to inform flexible ramp product procurement for the California ISO

How can independent system operators (ISOs) take advantage of probabilistic solar forecasts to lower generation costs and improve reliability of power systems? We discuss one three-step approach for doing so, focusing on how such forecasts might help the California Independent System Operator (CAISO) prepare unexpected net load ramps, where net load equals gross demand minus wind and solar production. First, we enhance an existing solar forecasting system to provide well-calibrated hours-ahead probabilistic forecasts. We then relate the degree of uncertainty reflected in the forecasted prediction intervals (independent variables) to error distributions for net load ramp forecasts for the CAISO real-time market (dependent variable) using machine learning and quantile regression. Projected ramp forecast errors conditioned on solar uncertainty are translated into flexible ramp requirements that therefore reflect real-time meteorological and solar conditions, improving on typical ISO procedures. Detailed descriptions are provided on the quantile regression and kth-nearest neighbor categorization methods for accomplishing that translation. Finally, a multiple time-scale look-ahead market simulation model is applied to a 118-bus IEEE Reliability Test System, modified to represent the CAISO generation mix and demand distributions. The model runs quantify how solar-conditioned ramp requirements can, first, decrease operating costs by reducing requirements compared to often conservative unconditional methods and, second, decrease generation scarcity events and consequently improve reliability by increasing flexibility requirements at times when unconditional forecast-based requirements understate actual ramp uncertainty. Solar-conditioned ramp requirements are found to reduce generation operating costs by about 2% for the test system (which would be equivalent to over $\$100$ million per year for a CAISO-size system).

14 SOLAR ENERGY↗