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At least 1,297 records · Page 72

Development of a water source heat pump hardware-in-the-loop (HIL) testing facility for smart building applications

Over the last decade, the global fight against climate change through electrification has led to an increase in research on building heating, ventilation, and air conditioning (HVAC) systems that utilize intelligent control algorithms to provide demand-side grid service while maintaining the thermal comfort of building occupants. As the pivotalpoint between building electricity consumption and indoor thermal comfort, high-efficiency electrical heatpumps are at the center of these emerging studies, and various grid-interactive and occupant-comfort control algorithms have been developed for them. The impact of these algorithms on the heatpump operation andperformance under different weather, building load, and grid requests calls for investigation and verification via experimental tests with actual heat pumps integrated with real-time building and grid responses. This study presents a Water-Source Heat Pump Hardware-in-The-Loop (HIL) Test Facility developed with the capability to perform such tests. The hardware configuration for this testfacility introduces a hydronic system that emulates the conditions for the heat pump water-side, and a duct system that emulates conditions for the heat pump airside. Both data acquisition and emulator control are implemented through the National Instruments (NI) LabVIEW software running on an NI PXIplatform. The HIL mechanism based on the hardware-software integration that allows the testbed to communicate with a generic simulation environment is also discussed. Currently, the test facility setup includes a single heatpump and virtual building model in EnergyPlus coupled with an occupant behavioral model in MATLAB. Preliminary test results of the current setup demonstrate the building load emulator's ability to track the simulated gone temperature with a Root Mean Square Deviation (RSME) below 0.12°C (0.216°F). An uncertainty analysis based on sensor accuracies shows that the heat pump coefficient of performance (COP) can be measured with a relative uncertainty of 10.4% in cooling and 3.7% in heating. Apartfrom the current testing on a single heat pump, the test facility also provides the flexibility to include additional heat pumps to form a heat pump cluster, as well as coupling the heat pump with active thermal storage to provide enhanced demandflexibility.

Calfa, Caleb↗

Second-generation downscaled earth system model data using generative machine learning

The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a generative machine learning approach called Super-Resolution for Renewable Resource Data (sup3r). This dataset builds on the first-generation Sup3rCC data by applying improved bias correction methods and adding downscaled precipitation to the output variables. As with the first Sup3rCC version, the data still include temperature, wind speed and direction at multiple heights, pressure, three components of downwelling solar radiation, and relative humidity—all at 4-kilometer (km) hourly resolution over the contiguous United States. This is a 25x spatial enhancement and 24x temporal enhancement of the source 100-km daily-average ESM data. This extension of the Sup3rCC dataset includes data from six ESMs from two shared socioeconomic pathways (SSPs) totaling 400 years of data with multiple future projections of changing meteorological conditions. The scenario selection was based on a structured evaluation of historical ESM skill and comprehensive representation of possible trajectories of future climate change in temperature, humidity, precipitation, solar irradiance, and near-surface wind speeds. The inclusion of multiple future projections is intended to enable users to assess key drivers of un 36 certainty and variability. All data are double-bias corrected, resulting in a product that can be used out-of-the-box for energy system analysis with minimal historical bias. The potential applications of Sup3rCC data extend to various topics in renewable energy resource assessment, energy systems modeling, and grid resilience studies. High-resolution future meteorological projections are critical for evaluating the effects of changing meteorological conditions on renewable energy generation, energy demand, and for optimizing energy storage and grid infrastructure. The 4-km hourly resolution of the downscaled data enables understanding of spatial and temporal variability at the scales necessary for energy system operational planning. In addition, the dataset can support risk assessments by providing detailed information on possible future extreme weather events and long-term meteorological variability at scales relevant to energy infrastructure. By offering an enhanced representation of possible future meteorological conditions, the second-generation Sup3rCC dataset enables more precise modeling of energy resilience and adaptation strategies in response to changing meteorological conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Modal test and analysis correlation

Modal testing plays a significant role in experimentally measuring the modal parameters used directly for response analysis of spacecraft or indirectly to update a mathematical model for use in response analysis. Developments in modal testing and correlation of results to analytical models are discussed. Several procedures to semi-automate correlation of resonant frequency and mode shape test data to the model have been shown to be valid for hypothetical problems but have not been successful in practice. Improving the correlation of frequencies and mode shapes does not necessarily improve the correlation of modal force coefficients. The paper discusses other parameters, such as kinetic energy and strain energy, which may be more significant in the correlation process. Because the most demanding requirement of a modal test is in determining dynamic loads, the authors asssume that objective, minimally discussing theoretical developments, summarizing their results, and giving sample data.

Wada, B. K.↗

The Ocean Colour Climate Change Initiative: II. Spatial and Temporal Homogeneity of Satellite Data Retrieval Due to Systematic Effects in Atmospheric Correction Processors

The established procedure to access the quality of atmospheric correction processors and their underlying algorithms is the comparison of satellite data products with related in-situ measurements. Although this approach addresses the accuracy of derived geophysical properties in a straight forward fashion, it is also limited in its ability to catch systematic sensor and processor dependent behaviour of satellite products along the scan-line, which might impair the usefulness of the data in spatial analyses. The Ocean Colour Climate Change Initiative (OC-CCI) aims to create an ocean colour dataset on a global scale to meet the demands of the ecosystem modelling community. The need for products with increasing spatial and temporal resolution that also show as little systematic and random errors as possible, increases. Due to cloud cover, even temporal means can be influenced by along-scanline artefacts if the observations are not balanced and effects cannot be cancelled out mutually. These effects can arise from a multitude of results which are not easily separated, if at all. Among the sources of artefacts, there are some sensor-specific calibration issues which should lead to similar responses in all processors, as well as processor-specific features which correspond with the individual choices in the algorithms. A set of methods is proposed and applied to MERIS data over two regions of interest in the North Atlantic and the South Pacific Gyre. The normalised water leaving reflectance products of four atmospheric correction processors, which have also been evaluated in match-up analysis, is analysed in order to find and interpret systematic effects across track. These results are summed up with a semi-objective ranking and are used as a complement to the match-up analysis in the decision for the best Atmospheric Correction (AC) processor. Although the need for discussion remains concerning the absolutes by which to judge an AC processor, this example demonstrates clearly, that relying on the match-up analysis alone can lead to misjudgement.

Ocean Colour↗

Transient Optimization of a Gas Turbine Engine

Gas turbine engines are the primary power plants for modern commercial aircraft. Transients prompted by significant changes in thrust or power demand are common and unavoidable. Extreme transient scenarios such as those associated with a go-around during a landing attempt are possible and must be accounted for in the design of the engine and its controller. Engine transients tend to cause a reduction in compressor operability margin, which must be addressed by the engine control system and accounted for in the engine design to prevent events such as compressor stall/surge and combustor blow out. Transient operability concerns typically lead to compromises in the engine design that sacrifice efficiency and/or limit responsiveness. Transient operability is typically managed by logic that limits the fuel flow command. If this logic is not optimized, then the potential for valuable performance could be lost. This study presents a strategy for optimizing the transient limit logic and proposes a strategy for updating the control logic over the lifespan of the engine. The results demonstrate significant improvements in transient operability. For example, of the results at sea level static conditions demonstrated a 31% reduction in the usage of the high pressure compressor operability stack during a snap acceleration transient. Furthermore, a reinforcement learning algorithm is demonstrated to modify the transient logic as the engine degrades to minimize response time while respecting a prescribed compressor operability margin limit. A simple demonstration of the reinforcement learning algorithm resulted in a thrust response time reduction of ~11.8%.

transient↗

Transient Optimization of a Gas Turbine Engine

Gas turbine engines are the primary power plants for modern commercial aircraft. Transients prompted by significant changes in thrust or power demand are common and unavoidable. Extreme transient scenarios such as those associated with a go-around during a landing attempt are possible and must be accounted for in the design of the engine and its controller. Engine transients tend to cause a reduction in compressor operability margin, which must be addressed by the engine control system and accounted for in the engine design to prevent events such as compressor stall/surge and combustor blow out. Transient operability concerns typically lead to compromises in the engine design that sacrifice efficiency and/or limit responsiveness. Transient operability is typically managed by logic that limits the fuel flow command. If this logic is not optimized, then the potential for valuable performance could be lost. This study presents a strategy for optimizing the transient limit logic and proposes a strategy for updating the control logic over the lifespan of the engine. The results demonstrate significant improvements in transient operability. For example, of the results at sea level static conditions demonstrated a 31% reduction in the usage of the high pressure compressor operability stack during a snap acceleration transient. Furthermore, a reinforcement learning algorithm is demonstrated to modify the transient logic as the engine degrades to minimize response time while respecting a prescribed compressor operability margin limit. A simple demonstration of the reinforcement learning algorithm resulted in a thrust response time reduction of ~11.8%.

transient↗

Transient Optimization of a Gas Turbine Engine

Gas turbine engines are the primary power plants for modern commercial aircraft. Transients prompted by significant changes in thrust or power demand are common and unavoidable. Extreme transient scenarios such as those associated with a go-around during a landing attempt are possible and must be accounted for in the design of the engine and its controller. Engine transients tend to cause a reduction in compressor operability margin, which must be addressed by the engine control system and accounted for in the engine design to prevent events such as compressor stall/surge and combustor blow out. Transient operability concerns typically lead to compromises in the engine design that sacrifice efficiency and/or limit responsiveness. Transient operability is typically managed by logic that limits the fuel flow command. If this logic is not optimized, then the potential for valuable performance could be lost. This study presents a strategy for optimizing the transient limit logic and proposes a strategy for updating the control logic over the lifespan of the engine. The results demonstrate significant improvements in transient operability. For example, of the results at sea level static conditions demonstrated a 31% reduction in the usage of the high pressure compressor operability stack during a snap acceleration transient. Furthermore, a reinforcement learning algorithm is demonstrated to modify the transient logic as the engine degrades to minimize response time while respecting a prescribed compressor operability margin limit. A simple demonstration of the reinforcement learning algorithm resulted in a thrust response time reduction of ~11.8%.

transient↗

An assessment of existing barriers to market adoption of thermal energy storage in buildings based on interviews with stakeholders

The United States administration recently established a goal of reducing greenhouse gas emissions by half below 2005 levels by 2030 and becoming a carbon-neutral economy by 2050. The transition to renewable energy sources may be significantly aided by energy storage. Energy storage could smooth the delivery of variable or intermittent renewable energy sources such as wind, hydro, and sun by storing excess renewable energy when it’s available and delivering it back when renewable energy production is low. Thermal energy storage (TES) is a way that stores thermal energy by heating or cooling a storage medium, which is then used for space heating and cooling, industrial processes, or power generation purposes later. This TES operation could lessen the demand for electricity in both the winter's and the summer's peak hours of electricity. While there are various studies that focus on the advancements and successes of TES technology, less attention is placed on its market adoption. Therefore, the current study undertakes survey-based interview research to understand the existing market barriers hindering TES application in buildings. A series of interviews were performed in this study with individuals from various backgrounds, ranging from homeowners to market specialists who work for TES manufacturers and utility companies. According to the responses obtained during the interviews, they strongly believe that TES has a high potential to contribute to the nation's grid stability and decarbonization goals, however, there are several barriers that prevent homeowners and heat pump manufacturers from investing in TES applications. The current study divided the responses from various background groups into categories to better understand the current challenges for TES applications in buildings. These responses range from payback concerns from homeowners to the need to develop a new metric to represent the benefits of TES from the heat pump and TES manufacturers. The findings from this study can be used by policymakers, utility companies, and manufacturers to better understand present obstacles and develop strategies to overcome them.

Prem Anand Jayaprabha, Jyothis Anand↗

Techno-economic feasibility of borehole thermal energy storage system connected to geothermal heat pumps for seasonal heating load of two buildings in Fairbanks, Alaska

Borehole thermal energy storage (BTES) is an effective solution for managing imbalanced heating and cooling loads in cold regions. This study evaluated the long-term feasibility of a BTES system in the Fairbanks area, Alaska, through building energy modeling, resource characterization, and numerical modeling. The system was designed to store waste heat from a nearby coal power plant during summer and provide thermal energy during winter to geothermal heat pumps supplying heating loads in two buildings. Heating load profiles were modeled for the buildings using EnergyPlus, and the results indicated the annual heating load was 5.6 times greater than the cooling load. 40 borehole heat exchangers were pre-designed approximately 100 m away from the two buildings in terms of land availability and regulatorily optimized depth. The 20-year performance of the designed BTES system under two operational scenarios—one with a 5-year preheating period and one without—was numerically modeled using subsurface temperature and properties characterized through the literature review and thermal response tests. Both scenarios demonstrated that the BTES has the capacity to fully cover the heating loads in the two buildings throughout the 20-year lifetime. Production temperatures at central wells were 33 % higher on average than at outer wells in both scenarios. The 5-year preheating period increased subsurface and extraction temperatures, and correspondingly annual average and total thermal energy production was higher for 8 years than in the scenario without the preheating period. These results highlight the long-term reliability and sustainability of the BTES system in meeting heating demands over its lifetime, with the preheating period offering potential performance improvements. Implementing the BTES system in cold regions with high heating demand, such as Fairbanks, Alaska, could provide a long-term, sustainable energy solution for managing imbalanced heating and cooling loads.

15 GEOTHERMAL ENERGY↗

Redox-Active Crown Ether Copolymer for Selective Lithium Recovery from Spent Lithium-Ion Batteries

The increasing demand for lithium, alongside concerns over resource scarcity and supply chain risks, has driven the need for alternative lithium sources, particularly from spent lithium-ion batteries (LIBs). Here, in this work, we introduce a redox-active crown ether copolymer designed for highly selective and electrochemically reversible lithium recovery from organic LIB leachates. A lithium-selective moiety, (12-crown-4)methyl methacrylate (12C4MA), is combined with a redox-active moiety, ferrocenylpropyl methacrylamide (FPMAm), into a redox copolymer electrosorbent to replace acid-based regeneration with electrostatic repulsion. The redox response enhances lithium ingress into the polymer, doubling lithium uptake (0.58 mol Li /mol CrE ) and enabling electrochemical regeneration upon the FPMAm oxidation. Our system exhibits exclusive lithium uptake, even in complex leachates containing competing metals (e.g., iron, nickel, and cobalt) and organic degradants. Techno-economic analysis highlights high energy efficiency and competitive lithium pricing to the market value (∼$12.7 per kg Li ). Overall, our work demonstrates a scalable, electrified adsorbent platform for sustainable and chemical-free critical metal recovery.

adsorption↗

Dynamic regulation of water potential in Juniperus osteosperma mediates ecosystem carbon fluxes

Summary Some plants exhibit dynamic hydraulic regulation, in which the strictness of hydraulic regulation (i.e. iso/anisohydry) changes in response to environmental conditions. However, the environmental controls over iso/anisohydry and the implications of flexible hydraulic regulation for plant productivity remain unknown. InJuniperus osteosperma, a drought‐resistant dryland conifer, we collected a 5‐month growing season time series ofin situ, high temporal‐resolution plant water potential () and stand gross primary productivity (GPP). We quantified the stringency of hydraulic regulation associated with environmental covariates and evaluated how predawn water potential contributes to empirically predicting carbon uptake. Juniperus osteospermashowed less stringent hydraulic regulation (more anisohydric) after monsoon precipitation pulses, when soil moisture and atmospheric demand were high, and corresponded with GPP pulses. Predawn water potential matched the timing of GPP fluxes and improved estimates of GPP more strongly than soil and/or atmospheric moisture, notably resolving GPP underestimation before vegetation green‐up. Flexible hydraulic regulation appears to allowJ. osteospermato prolong soil water extraction and, therefore, the period of high carbon uptake following monsoon precipitation pulses. Water potential and its dynamic regulation may account for why process‐based and empirical models commonly underestimate the magnitude and temporal variability of dryland GPP.

Plant Sciences↗

System Studies for Global Nuclear Assurance and Security (GNAS): 3S Risk Analysis for Portable Nuclear Reactors (Volume II) -- Conclusions and Implications

Growing interest in compact, easily transportable sources of baseload electricity has manifested in the proposal and early deployment of portable nuclear reactors (PNRs). PNRs are sought because they are scalable, efficient, and cost-effective for meeting energy demands in unique, remote, or contested areas. For example, Russia's KLT-40S Akademik Lomonosov is a floating nuclear power plant (FNPP) that successfully reached the Arctic coastal city of Pevek. It began providing power to the local grid in December 2019. While providing such key advantages as having a highly flexible power generation mechanism, FNPPs appear to directly challenge international norms and conventions for nuclear safety, safeguards, and security. FNPPs are neither a purely fixed nuclear fuel cycle activity nor a purely transportation-based nuclear fuel cycle activity. In response, Sandia's Mitigating International Nuclear Enogy Risks (MINER) research perspective frames this discussion in terms of risk complexity and the interdependencies between safety, safeguards, and security in FNPPs, and PNRs more generally. This systems study is a technically rigorous analysis of the safety, safeguards, and security risks of FNPP technologies. This research's aims are three-fold. The first aim is to provide analytical evidence to support safety, safeguards, and security claims related to PNRs and FNPPs (Study Report Volume I). Second, this study aims to introduce a systems- theoretic approach for exploring interdependencies between the technical evaluations (Study Report Volume II). The third aim is to show Sandia's ability for prompt, rigorous, and technical analysis to support emerging complex MINER mission objectives.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Ultra-high temperature stability Joule-Thomson cooler with capability to accomodate pressure variations

A Joule-Thomson cryogenic refrigeration system capable of achieving high temperature stabilities in the presence of varying temperature, atmospheric pressure, and heat load is provided. The Joule-Thomson cryogenic refrigeration system includes a demand flow Joule-Thomson expansion valve disposed in a cryostat of the refrigeration system. The expansion valve has an adjustable orifice that controls the flow of compressed gas therethrough and induces cooling and partial liquefaction of the gas. A recuperative heat exchanger is disposed in the cryostat and coupled to the expansion valve. A thermostatically self-regulating mechanism is disposed in the cryostat and coupled to the J-T expansion valve. The thermostatically self-regulating mechanism automatically adjusts the cross sectional area of the adjustable valve orifice in response to environmental temperature changes and changes in power dissipated at a cold head. A temperature sensing and adjusting mechanism is coupled to a cold head for adjusting the temperature of the cold head in response to the change in heat flow in the cold head. The temperature sensing and adjusting mechanism comprises a temperature sensitive diode, a wound wire heater, and an electrical feedback control circuit coupling the diode to the heater. An absolute pressure relief valve is interposed between the output of the cryostat and an exhaust port for maintaining a constant exhaust temperature in the refrigerating system, independent of the changes in atmospheric pressure.

Bard, Steven↗

Exploring the Utility-Privacy Trade-Off: Impacts of Semantic and Visit Types Ambiguities on Human Mobility Simulation

Humans are in perpetual movement, constantly traversing buildings, cities, waters, oceans, and countries. Mobility stands out as a major driving force shaping our modern societies. Capturing and explaining human behavior in a world of eight billion distinct mobility agendas is a complex challenge. With the rise of interconnected devices and platforms, such as smartphones, wearables, and point-of-interest data, largescale behavioral data has become more accessible, enabling rich insights into mobility patterns. However, the widespread availability of such data introduces significant ethical challenges. Detailed mobility data can inadvertently reveal sensitive personal information, including individuals' locations, habits, social interactions, and even political or religious affiliations. Beyond privacy breaches, the ethical implications of uncovering and potentially manipulating underlying behavioral patterns demand attention. Striking a balance between the utility of mobility models and the protection of individual privacy is therefore paramount. This paper explores the utility-privacy trade-offs in human mobility modeling, focusing on the impacts of introducing semantic and visit type ambiguities. By systematically examining how these ambiguities affect the fidelity of simulated trajectories and privacy risks, we provide a framework for evaluating ethical and privacy-conscious modeling practices. Our findings emphasize the need for methods that safeguard privacy without undermining the usefulness of mobility models, contributing to the responsible advancement of mobility science in alignment with ethical standards and societal expectations.

Amichi, Licia [ORNL] (ORCID:0000000177631394)↗

Biospecimen Culling: Temporal RNA Integrity Analysis Across Spaceflight Missions Dating from 1985 to 2011

The Ames Life Science Data Archive (ALSDA) at NASA Ames Research Center is managed by the Space Biosciences Division and has been operational since 1993. The ALSDA is responsible for archiving information and biospecimens collected from life science spaceflight experiments and matching ground control experiments. They are stored in the Ames biobank, which is located in the Biospecimen Storage Facility (BSF). The ALSDA also manages a Biospecimen Sharing Program, performs curation and long-term storage operations, and makes biospecimens available to the scientific community for research purposes via the Life Science Data Archive public website (https:lsda.jsc.nasa.gov). The BSF maintains both fixed and frozen spaceflight and ground tissues, collected from recent and past spaceflight missions. Due to the ever increasing demand for space to preserve current and future flight biospecimens, the ALSDA has initiated the development of a culling plan for biospecimens currently stored in the BSF. Culling enables the ALSDA to assess the quality of archived samples, and supports the development of standardized culling procedures that improve the operational efficiency of the BSF. The culling plan focuses on generating disposition recommendations for samples in the BSF, and currently is based on measuring ribonucleic acid (RNA) integrity number (RIN). The culling process includes (1) sorting and identification of candidate samples for RIN analysis, (2) completion of RIN analysis on select samples, and (3) development of disposition recommendations for specimens based on the RIN values. Furthermore, our approach allows for unique scientific opportunities, including development of a RIN-based methodology for culling, and temporal assessment of the quality of the tissues that have been stored in BSF since the 1980s. Results of this work will also support NASA open science initiatives.

biospecimen↗

Mitigations to Reduce the Law of Unintended Consequences for Autonomy and Other Technological Advances

The United Nations states that Earth’s population is expected to reach just under 10 billion people (9.7) by the year 2050. To meet the demands of 10 billion people, governments, multinational corporations and global leaders are relying on autonomy and technological advances to augment and/or accommodate human efforts to meet the required needs of daily living. Genetically modified organisms (GMOs), Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) gene-edited plants and cloning will be utilized to expand human food supply. Biomimetic implants are expected to improve life expectancy with 3D printed body parts. Human functioning will be extended with wearables and cybernetic implants continuing humanity’s path toward transhumanism. Families will be strengthened with 3 parent households. Disease will surely be eradicated using the CRISPR-CAS9 genetic engineering revolution to design out undesirable human traits and to design in new capabilities. With autonomous cars, trucks and buses on our roads and on-demand autonomous aircraft delivering pizzas, medical prescriptions and groceries in the air and multi-planet vehicles traversing space, utopia will finally arrive! Or will it? All of these powerful, man-made, technological systems will experience unintended consequences with certainty. Instead of over-reacting with hysteria and fear, we should be seeking answers to the following questions - “What skills are required to architect socially-healthy technological systems for 2050?” “What mindsets should we embody to ameliorate hubris syndrome and to build our future technological systems with deliberation, soberness and social responsibility?”

Morris, A. Terry↗

PINN surrogate of Li-ion battery models for parameter inference, Part I: Implementation and multi-fidelity hierarchies for the single-particle model

To plan and optimize energy storage demands that account for Li-ion battery aging dynamics, techniques need to be developed to diagnose battery internal states accurately and rapidly. Here, this study seeks to reduce the computational resources needed to determine a battery's internal states by replacing physics-based Li-ion battery models - such as the single-particle model (SPM) and the pseudo-2D (P2D) model - with a physics-informed neural network (PINN) surrogate. The surrogate model makes high-throughput techniques, such as Bayesian calibration, tractable to determine battery internal parameters from voltage responses. This manuscript is the first of a two-part series that introduces PINN surrogates of Li-ion battery models for parameter inference (i.e., state-of-health diagnostics). In this first part, a method is presented for constructing a PINN surrogate of the SPM. A multi-fidelity hierarchical training, where several neural nets are trained with multiple physics-loss fidelities is shown to significantly improve the surrogate accuracy when only training on the governing equation residuals. The implementation is made available in a companion repository (https://github.com/NREL/PINNSTRIPES). The techniques used to develop a PINN surrogate of the SPM are extended in Part II for the PINN surrogate for the P2D battery model, and explore the Bayesian calibration capabilities of both surrogates.

25 ENERGY STORAGE↗

Benchmark notch test for life prediction

Aircraft gas turbine engine components are subjected to severe stress, temperature, and environmental conditions. Economic and reliabilty demands have prompted inordinate effort in development of analytic methods to predict stresses and strains in aircraft engines. There remains, however, the need to check or verify these analytical methodologies against actual experimental data measurements. The laser interferometric strain displacement gage was recognized as having the potential to accomplish this task and was employed in this program. The actual strains incurred at the root of a discontinuity in cyclically loaded test samples subjected to inelastic deformation at high temperature where creep deformation readily occur were measured. The steady-state, cyclic stress-strain response at the root of the discontinuity in the tested samples was analyzed for comparison with the measured results. A comprehensive set of local notch root strain measurements for a variety of load patterns in an Inconel 718 notch specimen at 649 C (1200 F) was obtained and documented using the laser interferometric strain displacement gage.

Domas, P. A.↗