Load summary table for all sites
Summary peak load for all analyzed sites as part of study. The results are presented in 5 year increments
SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Summary peak load for all analyzed sites as part of study. The results are presented in 5 year increments
The NASA Advanced Composite Project (ACP), an industry/government/university partnership, has embarked upon the task of developing technology that can aid in reducing the time line for structural certification of aircraft composite parts using a combination of technologies, one of which is high fidelity damage progression computational methods. Phase II of this project included a task for validating an approach based on the Floating Node Method combined with Directional Cohesive Elements (FNM-DCZE). This paper discusses predicted damage onset and growth in a three-point bend doubler specimen compared to experimental results. Sensitivity of the simulations to mesh refinement as well as key material properties and thermal effects are studied and reported. Overall, qualitative results suggest the main aspects of the damage progression have been captured, with the simulated damage morphology and sequence of events resembling closely what was observed experimentally. Quantitatively, the first load-peak is predicted. However, the re-loading observed in the experiments, after the first load peak, is not captured numerically, suggesting further investigation may be worth pursuing.
A theoretical investigation was carried out to extend and improve an existing method for predicting the longitudinal characteristics of wing flap configurations with externally blown flaps (EBF). Two potential flow models were incorporated into the prediction method: a wing and flap lifting-surface model and a turbofan engine wake model. The wing-flap model uses a vortex-lattice approach to represent the wing and flaps. The jet wake model consists of a series of closely spaced vortex rings normal to a centerline which may have vertical and lateral curvature to conform to the local flow field beneath the wing and flaps. Comparisons of measured and predicted pressure distributions, span load distributions on each lifting surface, and total lift and pitching moment coefficients on swept and unswept EBF configurations are included. A wide range of thrust coefficients and flap deflection angles is considered at angles of attack up to the onset of stall. Results indicate that overall lift and pitching-moment coefficients are predicted reasonably well over the entire range. The predicted detailed load distributions are qualitatively correct and show the peaked loads at the jet impingement points, but the widths and heights of the load peaks are not consistently predicted.
A subscale solid laminate composite cylinder 31.5-in. diameter and 47.8 in. long with a [23/0/-23]4S layup known as NDL-1 was designed to fail in buckling and tested in axial compression to collapse twice. The proposed paper will focus on comparing the behavior of NDL-1 from the first test to failure (TTF-1) and the second test to failure (TTF-2). NDL-1 had a peak load of 466.3 kips during TTF-1 and a peak load of 390.4 kips, 15.5% lower, but with a similar stiffness, during TTF-2. Failure initiated at the 200º circumferential location in TTF-1, and at the 30º circumferential location in TTF-2. Though failure initiated at different locations, a similar radial deformation pattern was present just prior to collapse in TTF-1 and TTF-2. A shallow delamination occurred due to the initial failure event in TTF-1, and the damage had no influence on the response of NDL-1 during TTF-2. In the end, it was determined that NDL-1 failed in buckling during TTF-1 and TTF-2, and the second test to failure of NDL-1 highlighted interesting observations with respect to the effect of damage.
Structural integrity of composite systems under dynamic impact loading is investigated herein. The GENOA virtual testing software environment is used to implement the effects of dynamic loading on fracture progression and damage tolerance. Combinations of graphite and glass fibers with a toughened epoxy matrix are investigated. The effect of a ceramic coating for the absorption of impact energy is also included. Impact and post impact simulations include verification and prediction of (1) Load and Impact Energy, (2) Impact Damage Size, (3) Maximum Impact Peak Load, (4) Residual Strength, (5) Maximum Displacement, (6) Contribution of Failure Modes to Failure Mechanisms, (7) Prediction of Impact Load Versus Time, and (8) Damage, and Fracture Pattern. A computer model is utilized for the assessment of structural response, progressive fracture, and defect/damage tolerance characteristics. Results show the damage progression sequence and the changes in the structural response characteristics due to dynamic impact. The fundamental premise of computational simulation is that the complete evaluation of composite fracture requires an assessment of ply and subply level damage/fracture processes as the structure is subjected to loads. Simulation results for the graphite/epoxy composite were compared with the impact and tension failure test data, correlation and verification was obtained that included: (1) impact energy, (2) damage size, (3) maximum impact peak load, (4) residual strength, (5) maximum displacement, and (6) failure mechanisms of the composite structure.
In this work an integrated computational/experimental approach was developed to validate the predictive capabilities of State-of-the-Art (SoA) Progressive Damage Analysis (PDA) methods and tools. Specifically, a tapered composite structure incorporating ply-drops typical in the aerospace industry to spatially vary structural thickness was tested under static tension and cyclic tension fatigue loads. The data acquired from these tests included quantitative metrics such as pre-peak stiffness, peak load, location of delamination damage onset, and growth of delaminations as functions of applied static and fatigue loads. It was shown that the PDA tools were able to predict the pre-peak stiffness and peak load within ±10% of experimental average, thereby meeting and exceeding the pre-defined success criteria. Additionally, it was shown that the PDA tools were able to accurately predict the location of delamination onset and satisfactorily predict delamination growth under static tension loading. Overall, good correlations were achieved between modeling and experiments.
The effect of stress triaxiality on the strain-to-fracture of as-received and photo-oxidized polyamide-6 (PA-6) was investigated using mechanical testing, synchrotron X-ray tomography, and finite element analyses. Mechanical tests were conducted on cylindrical and round notched specimens, where different notch radii were used to vary the stress triaxiality. The specimens were aged by exposure to ultra-violet (UV) radiation at 60∘, causing photo-oxidation. As-received and so-aged specimens were loaded to failure (complete loss of load carrying capacity). For both unaged and aged specimens, a higher triaxiality led to a lower strain-to-fracture. To elucidate the micromechanical damage that mediates fracture in both conditions, specimens with an intermediate notch sharpness were loaded to the peak load, unloaded, and scanned ex situ using synchrotron X-ray tomography. Damage in the unaged bar was found to occur by cavitation and was concentrated at the center of the specimen, where the triaxiality is highest. In the UV-aged bar, a network of inter-connected chemical cracks were found on the notch surface, where the triaxiality is lowest. Finite element analyses were deployed to approximate the local triaxiality at damaged regions in the unaged and UV-aged specimens using a constitutive relation for semicrystalline polymers. From these analyses, the relationship between local triaxiality and strain-to-fracture was quantified for both unaged and photo-oxidized PA-6. Both unaged and photo-oxidized PA-6 showed similar decreases in ductility with triaxiality, hinting at common ductile fracture processes.
The use of a docking-system computer program in analyzing the dynamic environment produced by two impacting spacecraft and the attitude control systems is discussed. Performance studies were conducted to determine the mechanism load and capture sensitivity to parametric changes in the initial impact conditions. As indicated by the studies, capture latching is most sensitive to vehicle angular-alinement errors and is least sensitive to lateral-miss error. As proved by load-sensitivity studies, peak loads acting on the Apollo spacecraft are considerably lower than the Apollo design-limit loads.
NASA's Advanced Supersonic Parachute Inflation Research Experiments (ASPIRE) project was established to test full-scale supersonic parachutes at Mars-relevant conditions, as a risk-reduction activity for NASA's upcomingMars2020 mission. Deployment and inflation of Disk-Gap-Band (DGB) parachutes were examined at Mach number and dynamic pressure conditions relevant to Mars2020, using a sounding rocket platform. The flight tests examined two parachutes: a build-to-print version of the parachute used by the Mars Science Laboratory and a strengthened version of this parachute that has the same geometry but differs in materials and construction. The first flight test (SR01) of the built-to-print parachute took place on October 4, 2017, followed by the first test of the strengthened parachute during flight SR02 on March 31, 2018. A second test of the strengthened parachute with a higher target load, SR03, took place on September 7, 2018. Over the sequence of the three tests, the parachute was exposed to increasing aerodynamic loads with the peak load during SR03 being significantly larger than is expected during a Martian descent. All three tests were successful: the parachute deployment and inflation occurred at the intended conditions, the measurement systems performed as designed and provided the data, and the parachutes survived the aerodynamic loads they were exposed to. The flight tests yielded valuable data on parachute forces and high-speed imagery of the deployment and inflation process.
A thermal aging vessel instrumented with load cells was fabricated. The primary function of the vessel is to continuously monitor the in situ load retention of up to three compressed polymer coupons undergoing thermally accelerated aging under nitrogen. A secondary function is to enable gas sampling of the vessel headspace during thermal aging. Heating of the vessel is achieved using a custom heater jacket. To improve upon our conventional aging study methods which require periodic interruption of aging to perform load testing in an Instron machine at room temperature, this technology aims to automate/facilitate data acquisition/analysis, improve data quality, and enable uninterrupted compression of the polymer which represents the service condition. As an example case to assess functionality of the in situ vessel, the load retention of a siloxane elastomer material additively manufactured by direct-ink-writing (DIW) was measured at three different isothermal aging temperatures for ~1 month. Initial compression of the coupons while near the aging temperature was achieved by temporarily opening the heated vessel to access the interior chamber and manually tightening four nuts to drive the heated compression plate down onto the heated coupons. Initial testing demonstrated achievement of the primary load retention monitoring function. Unfortunately, the vessel leaked which prevented gas sampling; an active purge was used to maintain a nitrogen atmosphere. Welded or otherwise sealed joints, which could be implemented in a future design, would likely eliminate leak paths. To apply time-temperature superposition (TTS), a technique used to provide long-term prediction of the load retention from short-term isothermal data, the load retention needed to be calculated relative to the load at an estimated “equilibrium” time, after most of the transient viscoelastic physical relaxation occurred. The peak load immediately after compression could not be used as the load retention basis for two reasons: (1) age-related changes must be isolated from non-age-related physical relaxation before applying TTS and (2) the manual mechanism used to compress the specimens at the aging temperature was neither smooth nor repeatable which affected the peak load value. To better understand the effect of the mode of initial compression on the measured load, and possibly better estimate “equilibrium” physical relaxation times, systematic stress relaxation experiments were performed using an Instron machine with a thermal chamber. At a given temperature, the DIW polymer was compressed to a fixed strain in either a stepped or continuous manner at two different rates, then held at that strain for 24 hrs. The results indicated that, at a given temperature, the different stress relaxation curves appeared to converge to the same curve at some “equilibrium” time when the non-age-related physical relaxation was mostly complete. Though this observation suggests that the discontinuous manual compression employed by the vessel is feasible, a compression mechanism that is rapid, smooth, and repeatable would enhance its use.
The load profile for domestic water heating is time-dependent and can result in high energy demand during peak operating times. Shifting this peak load can have significant environmental and economic impacts. Phase change material (PCM)-based thermal energy storage (TES) is a potentially useful technology for peak load shifting in domestic hot water (DHW) applications thanks to its high latent heat and energy density. In this study, an annular finned-tube PCM-HX design concept was optimized for a load-shifting TES unit to meet the Department of Energy standard for a medium-usage DHW heater using a resistance-capacitance model (RCM) integrated with a Multi-Objective Genetic Algorithm. The optimized design comprised 70 identical annular finned-tube PCM-HX units connected in parallel and utilizing RT62HC as the PCM. A single PCM-HX unit was prototyped and tested in a vertically oriented setup with upward heat transfer fluid (HTF) flow. The hot water supply time was defined based on a cutoff temperature of 51.7°C. The as-designed mass flow rate (1.5 g/s) was tested to assess the performance of the prototyped PCM-HX unit for RCM validation. For the experimental investigation, RTD sensor bundles measured HTF temperature at the PCM-HX inlet and outlet, and a Coriolis flow meter accurately measured the HTF mass flow rate. The simulated discharging power underpredicted the experimental result by about 12%, and the simulated hot water supply time underpredicted the experimental result by approximately 13% for the as-designed mass flow rate (1.5 g/s). The average deviation of the hot water supply temperature between the experimental and RCM results during the complete PCM solidification process was 1.3 K for the as-designed mass flow rate. The overall good agreement between the experimental and RCM results provides confidence that computationally efficient models such as RCM can be utilized for design optimization of PCM-HXs.
Electricity load forecasting is essential to utility operation and power grid stability. A wide spectrum of data-driven methods, ranging from linear regression models to more recent deep learning models have been adopted to forecast electric load over the years. However, there still lacks a holistic evaluation of the applicability of conventional statistical and machine learning based algorithms with respect to different temporal and spatial scopes, computational requirements, and sensitivity of model-tuning. Enabled by a large-scale electricity load profile dataset of over 40,000 residential customers in a utility region, we conducted a cross-dimensional analysis of data-driven load forecasting methods. Three regression-based and seven deep learning algorithms with different model configurations were evaluated in terms of their overall and peak load prediction accuracy, and training burdens, across spatial aggregation levels ranging from the transformer, feeder, substation, to neighborhood. We found, first, the load forecasting accuracy is constrained by a predictability boundary, influenced by the forecasting horizon and spatial aggregation level. Specifically, RandomForest, XGBoost, TFT, TSMixer, and TiDE models achieved less than 10 % prediction error for up to 96-h ahead forecasting for district, substation, and feeder levels, while other models struggle at long-horizon predictions; Second, for winter and summer peak load dates, most models were able to predict the peak demand timing within ± 1 h, but the prediction percentage error varied by models, with TFT and TiDE models being the top performers; Third, models with similar prediction accuracy can differ in training burden by an order of magnitude. Therefore, choosing model configurations that balance prediction performance and computational resource is an important practical consideration for large-scale deployment of the machine learning based load forecasting. The outcome of this study can guide researchers and practitioners to choose the proper load forecasting algorithms based on their problem scope, required accuracy, and available resources. The predictability boundary can serve as a benchmark for electricity load forecasting problems with new algorithms and datasets.
Cycle life studies have been performed at Eagle Picher Technologies (EPT), on HST Mantech design cells with various pedigrees of slurry and dry sinter processed electrodes, to evaluate peak load voltage performance during generic load profile testing. These tests provide information for determining voltage and capacity fade (degradation) mechanisms, and their impact on nickel hydrogen cell cycle life. Comparison of peak load voltage fade, as a function of State of Charge and cycle life, with capacity data from HST indicates that the cycle life limiting mechanism is due to impedance growth, and formation of a second discharge plateau. With a second plateau on discharge, capacity from the cell is still available, but at an unacceptable low voltage of 0.8 V per cell (17.6 V battery). Data shows that cell impedance increases with cycle number and depth of discharge, as expected.
Charge management, which lowers charging costs for fleets and prevents straining the electrical grid, is critical to the successful deployment of medium- and heavy-duty battery-electric trucks (MHD BETs). This study introduces an energy demand and cost management framework that optimizes depot charging for MHD BETs by combining an energy consumption machine learning model and a linear program optimization model. The framework considers key factors impacting real-world MHD BET operations, including vehicle and charger configurations, duty cycles, use cases, geographic and climate conditions, operation schedules, and utilities’ time-of-use (TOU) rates and demand charges. The framework was applied to a hypothetical fleet of 100 MHD BETs in California under three different utilities for 365 days, with results compared to unmanaged charging. The optimized charging solution avoided more than 90% of on-peak charging, reduced fleet charging peak load by 64–75%, and lowered fleet energy variable costs by 54–64%. This study concluded that the proposed charge management framework significantly reduces energy costs and peak loads for MHD BET fleets while making recommendations for fleet electrification infrastructure planning and the design of utility TOU rates and demand charges.
The Progressing Analysis of Variable Electric Rates (PAVER) study analyzed the impact of a range of time-varying electric rates on the performance of a regional electric grid and the resulting costs for participating and non-participating customers. This analysis leveraged and extended the work of PNNL’s Distribution System Operator with Transactive (DSO+T) study. Five different rate designs were included: a flat volumetric energy charge, a typical Time of Use (TOU) rate, a dynamic energy (DE) rate (based on wholesale locational marginal prices), a dynamic energy and capacity (DE+C) rate, and, finally, a Block and Swing (B&S) rate that billed customers based on their average load profile at constant pricing, but used the DE+C dynamic price for load deviations from their average profile. These rates were analyzed in a large-scale co-simulation of an entire regional grid with a customer population representative of the current state. A large fraction (80%) of residential and commercial customers were assumed to participate in these time-varying rates with automatically controlled HVAC, water heaters, electric vehicles, and batteries. This study assumed no industrial sector participation. The DE and DE+C rates saw system peak loads reduced by 6-7%, while the large participation in the TOU rate case saw a significant rebound effect and a resulting peak load increase of >5%. The impacts to the annual and peak system demand impacted system wholesale prices and the overall grid operating costs. This cost structure determined the revenue needed to be collected from customers by each rate design. Participating customers on the DE and DE+C rates (located in one of the modeled DSOs) saw reductions in average annual electricity bills of 11-17% with average increases in monthly bill variation of no more than 13%. At such high participation levels, TOU customers saw 10% higher average annual bills (due to system-wide rebound effects) and average increased monthly bill variation of 16%. Residential owners of large flexible loads (such as electric vehicles) saw larger bill savings (17-20%) when on a fully dynamic rate. The presence of on-site generation (such as rooftop solar) did not appear to appreciably change customer outcomes. Customers on the Block and Swing rate did see 6% lower monthly bill variation (as intended) than the flat rate case, but at the expense of appreciable bill savings, which were only 3%, comparable to the savings seen by non-participants. Given this finding we recommend that additional research be conducted into how best various bill protection mechanisms can balance minimizing customer bill variation with providing financial incentives commensurate with the flexibility customers provide. We also recommend that customer outcomes be explored across a range of regions using current actual customer and system cost data.
Validation of a progressive damage finite element analysis model using the CompDam material model was performed on a large multi-stringer panel subjected to compressive loading. The panel had a Teflon insert embedded between the skin panel and stiffener to cause an ultimate failure mode of stiffener separation. The compressive loading of the panel caused the skin between the stiffeners to locally buckle before any damage began to occur. The post-buckled behavior of the panel was the driving mechanism to the onset of damage and the damage growth that led to skin-stiffener separation. An integrated global-local modeling approach was used to validate several aspects the overall behavior of the panel from start to failure. The global region captured the pre-buckled stiffness of the test panel within 10% and the buckling load of the skin panel at the critical location within 2%. The skin’s five half-wave buckled mode shape was accurately predicted by the model. The integrated local model captured the load corresponding to the onset of damage within 5% of the average test data. Comparisons are made for key aspects of the damage morphology, such as a growth pattern that included a significant matrix split in the first ply of the skin and a migration of the delamination from the skin-stiffener interface to the skin’sply1-ply2 interface. The ultimate failure mode was shown to be an unstable growth of delamination damage under the stiffeners which led to a peak load of the analysis that was approximately 5% above the average peak load of the testing. The validated global-local modeling approach used on the multi-stringer post-buckled panel with a Teflon insert used a methodology and lessons learned using smaller specimens applied to a subcomponent that captured several aspects of a modern aircraft design.
The global room air conditioner (AC) industry has undergone rapid growth, and the U.S. and India now face new supply chain risks due to China’s dominant role in manufacturing and driving demand. As India’s room AC market and related electricity consumption increases with continued economic development, it faces dual challenges of supply chain vulnerabilities and power grid blackouts from higher peak loads. To mitigate supply chain vulnerabilities for high-efficiency cooling equipment and critical mineral inputs to AC components, there is an increasing need to diversify the supply chain and address energy security and peak load risks to both the U.S. and India. This report assesses the potential for diversifying supply chains and scaling up manufacturing of highly efficient cooling equipment technologies and related critical mineral inputs in the U.S. and India. Successful cooperation on these technologies will enable the U.S., India, and their Quadrilateral Security Dialogue (Quad) partners to diversify AC supply chains while meeting India’s large and growing demand for efficient cooling. In the similarly concentrated supply chain for critical minerals, the U.S. and India can work with Japan and Australia to leverage each country’s strengths in diversifying mining, processing, and refining while pursuing alternatives to materials with high supply chain risks and supporting increased recycling and circular economy approaches.
Here, the thermally anisotropic building envelope (TABE) is a novel active building envelope that enhances energy efficiency and thermal comfort in buildings by transferring heat and cold between building envelopes and hydronic loops. When coupled with thermal energy storage (TES) units, the TABE + TES enables the storage of both heat and cold energy captured by the TABE roof or exterior walls. This stored energy can be later released by the TABE floor for indoor heating and cooling, benefiting both the grid and the end user. This paper evaluates the merits of TABE + TES for building demand-side management across various US climate conditions, focusing on peak load shaving, annual energy savings, and cost savings under time-of-use (TOU) electric rate schedules. Simulations were conducted by integrating time-of-day–informed, rule-based control strategies in MATLAB, TABE components and TES units in COMSOL Multiphysics, and whole-building energy analysis in EnergyPlus. A case study using the US Department of Energy’s prototype single-family detached house model in Birmingham, Alabama; Los Angeles, California; Oak Ridge, Tennessee; and Denver, Colorado, showed that the TABE + TES system achieved (1) 70 % peak load shaving in Los Angeles and Denver and 20 % in Birmingham and Oak Ridge; (2) significant peak electricity savings of 351–497 kWh, reducing peak energy consumption by 38 %–78 %; and (3) annual heating cost savings of 0.79 $\$$/m2–1.17 $\$$/m 2 and cooling cost savings of 0.60 $\$$/m 2 –1.17 $\$$/m 2 using a normal utility rate or low-TOU rate. The benefits of employing the TABE + TES system are even more significant under high TOU rates.