Search NASA⌕ Search

SEARCH · Search NASA

Results for “load calibration”

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.

At least 163 records · Page 9

Capability of Impedance Measurement Using Spread Spectrum Time-Domain Reflectometry

Spread spectrum time-domain reflectometry (SSTDR) has been proposed for measuring electrical impedance on live, energized systems, in electrically noisy environments, or for measuring multiple channels simultaneously. Here we evaluate the capability of SSTDR for impedance measurement from near dc to 96 MHz and find that they agree very well with measurements from a vector network analyzer (VNA). Time gating is used to remove (calibrate out) transmission line effects. We evaluate the frequency ranges over which SSTDR at different modulation frequencies is accurate for the measurement of series resistive–capacitive ( RC ) loads and observe that fusing measurements from multiple modulation frequencies can broaden the effective measurement bandwidth.

14 SOLAR ENERGY↗

Dynamic modeling of heat pipe integrated thermal battery latent heat storage system experiment validation

A heat pipe integrated thermal battery system has been constructed to investigate a high-temperature latent heat thermal energy storage technology that takes advantage of near isothermal operation of latent heat storage and heat pipes to potentially enable high-energy isothermal heat storage. A dynamic model constructed in Modelica has been validated, showing errors between 2.5 °C–39.7 °C across 10-h to 47-h simulations against experiment results, showing good prediction capability of experiment output, especially against phase change time. Model calibrations showing vessel heat-up capability of 3 kW and heat pipes combining to provide 600 W each during experiment operation validate experiment circumstances including reduced material loading and reduced power capability. The experiment configuration uses an Al-Mg-Zn eutectic metal as the storage material, heated via heat tape wrapped around the vessel and guide tubes to bring the system to operation range (>400 °C) and to simulate charging heat exchange, respectively, with heat rejection occurring through the surfaces of the material and facilitated via guide tubes with less insulation wrapping. The model is available in the open-source repository HYBRID on Github.

25 - ENERGY STORAGE↗

Failure Strain and Related Triaxiality of Aluminum 6061-T6, A36 Carbon Steel, 304 Stainless Steel, and Nitronic 60 Metals, Part I: Experimental Investigation

The objective of this study is to develop failure-limit material models for Aluminum 6061-T6, A36 Carbon Steel, 304 Stainless Steel, and Nitronic 60 metals, based on parameters of plastic equivalent strain (failure strain) and stress triaxiality. The research is conducted in two parts. This paper presents Part One of the study. In Part One, custom-designed test specimens undergo controlled uniaxial tension and compression testing at ambient temperature. These tests are performed at quasi-static speeds using Universal Testing Machines (UTMs) in accordance with ASTM E8 and ASTM E9 standards. Experimental data, specifically engineering stress–strain and force–displacement curves, are recorded from the onset of loading until specimen fracture, or in the case of compression tests, until the capacity of the testing machine is reached. In Part Two, the emphasis shifts to the calibration of Finite Element Analysis (FEA) models of the custom-designed test specimens. Plastic equivalent strain and the corresponding stress triaxiality values at failure are extracted from each test specimen for the given metal. These values are then systematically plotted onto a single graph to construct the failure-limit curve, which delineates the boundary conditions for material failure. This approach will facilitate the development of a comprehensive material property definition that correlates plastic equivalent strain with stress triaxiality at failure for Aluminum 6061-T6, A36 Carbon Steel, 304 Stainless Steel, and Nitronic 60 metals.

Harwell, Ron↗

A practical extension of the recursive multi-fidelity model for the emulation of hole closure experiments

We report in regimes of high strain rate, the strength of materials often cannot be measured directly in experiments. Instead, the strength is inferred based on an experimental observable, such as a change in shape, that is matched by simulations supported by a known strength model. In hole closure experiments, the rate and degree to which a central hole in a plate of material closes during a dynamic loading event are used to infer material strength parameters. Due to the complexity of the experiment, many computationally expensive, three-dimensional simulations are necessary to train an emulator for calibration or other analyses. These simulations can be run at multiple grid resolutions, where dense grids are slower but more accurate. In an effort to reduce the computational cost, a combination of simulations with different resolutions can be combined to develop an accurate emulator within a limited training time. We explore the novel design and construction of an appropriate functional recursive multi-fidelity emulator of a strength model for tantalum in hole closure experiments that can be applied to arbitrarily large training data. Hence, by formulating a multi-fidelity model to employ low-fidelity simulations, we were able to reduce the error of our emulator by approximately 81% with only an approximately 1.6% increase in computing resource utilization.

36 MATERIALS SCIENCE↗

Assessing Nutrient and Carbon Responses to Agricultural Conservation Practices in Two Midwest Watersheds

The United States is undertaking efforts to transition to a low-carbon economy in response to the heightened impacts of climate change, which are largely attributed to decades of carbon-intensive development. A concerted effort by the energy sector to achieve net-zero carbon emissions is aimed at strategically reducing the carbon footprint of the energy supply chain, particularly in the production of feedstocks for biofuels. The production of biofuels relies heavily on land use and management practices in biomass cultivation. Among other factors, soil organic carbon (SOC) plays a crucial role in the biofuel carbon cycle, impacting land productivity, greenhouse gas emissions, and water quality. The process of carbon drawdown during plant growth and storage helps to mitigate the release of carbon dioxide (CO 2 ) into the atmosphere. Another key parameter is the release of nitrous oxide (N 2 O) — a potent greenhouse gas with a global warming potential 273 times that of CO 2 — from soil. While prioritizing low-carbon production, sustainable bioenergy also necessitates improved water quality and ecosystem services. Agricultural conservation practices can contribute to enhanced soil health and reduce nutrient and sediment loss into streams. However, studies that explore the broader impact of these practices on soil carbon storage and N 2 O emissions at a watershed scale are limited. Specifically, our understanding of how low-carbon feedstock production and management affect nutrient cycle dynamics is incomplete. This study assesses watershed responses to land management practices in two agriculturally dominant watersheds: the Raccoon River watershed and the Southfork of Iowa River watershed. The study focuses on carbon and nutrient dynamics, characterizing spatial and temporal variations in SOC, N 2 O, and nutrient loadings to examine the relationship between nutrient and carbon responses and agricultural conservation practices. The study employs the newly developed Soil Water Analysis Tool for Carbon (SWAT-C) model, calibrated using 20 years’ of climate and water monitoring data, to simulate and evaluate two agricultural conservation practices: no-till and crop residue harvest with cover crop planting. We compared the calibrated SWAT-C model with a historical baseline model, which allowed us to analyze various aspects of the watershed, including stream flow, suspended sediments, nitrogen, phosphorus, organic carbon, SOC at different depths, and N 2 O emissions from topsoil. Our SWAT-C modeling results indicate that, compared with results from the historical baseline model, no-till practices are positively correlated with SOC accumulation, reduced N 2 O emissions, and decreased soil loss. We also observed no change or slightly increased nitrogen and phosphorus loss to water bodies in the watersheds compared with the baseline. Conversely, crop residue harvest with cover crop planting improved water quality by reducing nutrient and soil losses but also increased N 2 O emissions. This SWAT-C modeling study establishes the groundwork for further smaller-scale and/or sub-basin-level assessments of nitrogen, phosphorus, and carbon cycles. It provides valuable science-based insights to inform policy decisions — particularly in the context of transitioning to biofuel feedstock production in these watersheds — by addressing concerns about nutrient exports to local water bodies and, ultimately, the Mississippi River.

54 ENVIRONMENTAL SCIENCES↗

Comparative Analysis of ANN and LSTM Prediction Accuracy and Cooling Energy Savings through AHU-DAT Control in an Office Building

This paper proposes the optimal algorithm for controlling the HVAC system in the target building. Previous studies have analyzed pre-selected algorithms without considering the unique data characteristics of the target building, such as location, climate conditions, and HVAC system type. To address this, we compare the accuracy of cooling load prediction using ANN and LSTM algorithms, widely used in building energy research, to determine the optimal algorithm for HVAC control in the target building. We develop a simulation model calibrated with actual data to ensure data reliability and compare the energy consumption of the existing HVAC control method and the two algorithms-based methods. Results show that the ANN algorithm, with a CV(RMSE) of 12.7%, has a higher prediction accuracy than the LSTM algorithm, CV(RMSE) of 17.3%, making it a more suitable algorithm for HVAC control. Furthermore, implementing the ANN-based approach results in a 3.2% cooling energy reduction from the optimal control of Air Handling Unit (AHU) Discharge Air Temperature (DAT) compared to the fixed DAT at 12.8 °C in a representative day. This study demonstrates that ML-based HVAC system control can effectively reduce cooling energy consumption in HVAC systems, providing an effective strategy for energy conservation and improved HVAC system efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Estimating the value of jointly optimized electric power generation and end use: a study of ISO-scale load shaping applied to the residential building stock

A generation-to-load simulation estimated the impact, in terms of production costs and CO2 emissions, attributable to the joint optimization of electric power generation and flexible end uses to support increasing penetrations of renewable energy. Newly conceived, evaluated, and foundational in developing a U.S. National Standard was a transaction-less yet continuous demand response system based on a day-ahead optimum load shape (OLS) designed to encourage Internet-connected devices to autonomously and voluntarily explore options to favour lowest cost generators - without requiring two-way communications, personally identifiable information, or customer opt-in. Boundary conditions used for model calibration included historical weather, residential building stock construction attributes, home appliance and device empirical operating schedules, prototypical power distribution feeder models, thermal generator heat rates, startup and ramping constraints, and fuel costs. Results of an hourly-based annual case study of Texas indicate a 1/3 reduction in production costs and a 1/5 reduction in CO2 emissions are possible.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Detection of significant antiviral drug effects on COVID-19 with reasonable sample sizes in randomized controlled trials: A modeling study

Development of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials. A modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d -1 (95% CI: 1.06 to 1.27 d -1 ), 0.777 d -1 (0.716 to 0.838 d -1 ), and 0.450 d -1 (0.378 to 0.522 d -1 ) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies). Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome. We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation. In this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

60 APPLIED LIFE SCIENCES↗

The GammaSpec Package for Automated Gamma-ray Analysis (V.1.0)

This report describes the GammaSpec package, a tool developed to automate the analysis and comparison of gamma-ray spectra. The goal of this tool is to drastically reduce, or even eliminate, currently time consuming processes for comparing large sets of gamma-ray measurements. There are a number of potential applications for this work throughout the laboratory, but particularly within Global Security. Current work flows where large numbers of measured spectra must be compared for anomolies and outliers often consist of loading and visually inspecting individual spectra, or utilizing small-batch tools. One such example is the PeakEasy tool also developed at LANL. PeakEasy has a robust and tested feature set for calibrating, identifying, and fitting gamma-ray spectra. However it’s intention was not for batch processing and automated comparison of large numbers of spectra. This tool is not intended to replace PeakEasy in an analyzers arsenal, but to instead augment it. The intention here is to automate the isolation of spectra of particular interest, which can then be studied in further detail. This report is arranged as follows. Section 2 lays out the design goals and desired functionality of the package. Section 3 describes the algorithms developed and chosen to accomplish those goals. Section 4 describes the primary interaction with the tool, as well as it’s resulting output. Following these sections, results are presented from a set of example datasets from High Purity Germanium (HPGe) detectors in Sec. 5. Finally, the current status is summarized in Sec. 6.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Plutonium-238 Loadout Calorimeter Return To Service

The calorimeter in the transfer area in Building 7920 at the US Department of Energy’s Oak Ridge National Laboratory is used to measure the amount of 238 Pu in the Plutonium Heat Source Oxide. The calorimetry measurement is taken after the oxide is packaged in an ORISC (Oak Ridge Inner Shipping Capsule)/FSO (Fuel Storage Outer) assembly before loading into the Containment Vessel and shipping container. The equipment is used in three specific configurations: zero measurement (nothing in the sample cup), FSO measurement (actual measurement of 238 Pu), and reference calibration measurement (using the reference FSO as a known heat source). System checks were performed in July 2023 in preparation for scheduled material loadout. During these checks, personnel discovered that the reference FSO had experienced an electrical short in the heater cable and was no longer functional. The calorimeter was in the reference calibration measurement configuration at this time. Facility management was notified when the damage was discovered. The data from the Yokogawa recorder were pulled and analyzed for a span of time between September 2022 and July 2023. An unusual spike was found in the sample cup temperature data that started on October 19, 2022, and ended on October 20, 2022. The sample cup reached a temperature of 191.1°C. The maximum allowable temperature for the calorimeter thermopile to reach is 220°C based on the manufacturer statement provided in Appendix B of this report [1]. The calorimeter thermopile and the sample cup thermocouple are physically close to each other; therefore, the data suggest that the calorimeter itself never saw a temperature in excess of 191.1°C. Physical damage present on the cable, tape, and insulation suggests that the temperature reached a higher value in some locations within the sample cup than the data shows. Because of this discrepancy, testing of the calorimeter was required to confirm that the calorimeter is functioning the same as it was before the electrical short. The intent of this report is to assess the functionality of the calorimeter and determine if it is acceptable to use for 238 Pu loadout material measurement. Testing showed that the calorimeter is functionally equivalent to the initial calibration that was performed in the summer of 2021, and thus, the calorimeter was cleared to be used for its intended purposes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗

Load dynamics of double planar foil liners and double planar wire arrays on the UM MAIZE LTD generator

In previous studies using the University of Nevada, Reno's (UNR's) high-impedance Zebra Marx generator (1.9 Ω, 1.7 MA, 100 ns), Double Planar Wire Arrays (DPWAs) proved to be excellent radiators, and Double Planar Foil Liners (DPFLs) proved useful for future inertial confinement fusion applications. This article presents the results of joint UNR/UM (University of Michigan) experiments with aluminum (Al) DPWAs, Al DPFLs, and tungsten (W) DPWAs using UM's Michigan Accelerator for Inductive Z-Pinch Experiments (MAIZE) generator, a low-impedance Linear Transformer Driver (LTD) (0.1 Ω, 0.5–1 MA, and 100–250 ns). The main goals of this study were twofold: the first was a pioneering effort to test whether a relatively heavy Al DPFL could successfully be imploded on a low-impedance university-scale LTD like the MAIZE generator, and, if so, to analyze the results and make comparisons to the optimized, lighter DPWA configurations that have been previously studied. The DPWAs consisted of two planes of micrometer-scale diameter Al or W wires, while the DPFLs consisted of two planes of micrometer-scale thickness Al foils. Diagnostics include filtered Si-diodes, an absolutely calibrated filtered PCD, x-ray pinhole cameras, spectrometers, and gated optical self-emission imaging. The implosion dynamics and radiative properties of Al DPWAs and DPFLs and W DPWAs on the MAIZE LTD are discussed and compared. Time-dependent load inductance calculations derived from measurements of the load current and a MAIZE circuit model provide a relative measurement of pinch strength. In experiments on MAIZE, W planar wire arrays exhibited a higher peak load inductance throughout the pinch than Al DPWAs and DPFLs, while x-ray pulses from Al DPFLs had the longest emission duration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Design, development and commissioning of a multi-alkali semiconductor photocathode deposition system for the IUAC Delhi light source photoinjector

A fourth-generation light source, called Delhi Light Source (DLS) based on photocathode-based RF gun has been commissioned at Inter-University Accelerator Centre, New Delhi. Presently, the electron beam is being generated from copper photocathode and the beam is being used for scheduled experiments. Soon, the semiconductor photocathode will be used to produce higher beam current. Here, to develop the semiconductor photocathode, a dedicated photocathode deposition facility was developed in collaboration with Brookhaven national Laboratory (BNL) and has been successfully commissioned and becomes operational at IUAC. This deposition facility is an integrated system with the electron gun and is a unique system as it is capable of producing, preserving (without residual gas poisoning) and in-vacuum transfer of the deposited photocathodes from the deposition chamber up to the RF electron gun. The system is designed to operate under ultra-high vacuum (UHV) and is equipped with load-lock chambers, substrate heating assembly, thickness monitoring via a quartz crystal microbalance (QCM), and an in-situ setup for quantum efficiency (QE) measurements. After testing of all the subsystems and a detailed calibration, the first deposition of a cesium telluride (Cs 2 Te) photocathode was successfully performed on a copper (Cu) substrate. This successful commissioning and initial deposition mark a significant step toward the indigenous photocathode development and lays the groundwork for further research into advanced photo emissive materials at IUAC. This paper will discuss the salient features, installation, commissioning, first semiconductor photocathode deposition and its results.

47 OTHER INSTRUMENTATION↗

Analyzing Mechanical integrity of Microwave resonant Cavity flowmeter

The microwave resonant cavity flow sensor has been proposed to address the difficulties of measuring high-temperature molten salt flow in reactor vessels. The flow sensor consists of a metallic cylindrical cavity coupled to a microwave waveguide. The cylindrical cavity has one of the flat surfaces thin enough to undergo microscopic deflection due to dynamic pressure of the exerted by the flowing fluid. Deflection of the membrane causes a shift in the microwave resonant frequency. Fluid velocity can be estimated from the calibration curve. The objective of this report is to investigate mechanical integrity of the flowmeter’s membrane. The membrane is a thin stainless-steel circular plate with a clamped edge, subjected to uniform load. By calculating the stress on the plate due to deflection and, comparing the stress to the material ultimate tensile strength and yield strength, it can be estimated if the plate will fail. If the maximum stress is greater than the yield strength, the plate will undergo plastic deformation, and the sensor will be disabled. A stress greater than the ultimate tensile strength will cause the plate to fracture. The stress on the plate was calculated with an analytic closed form solution model, and with COMSOL Structural Mechanics Module which does not involve any approximations. Stresses in both the analytic model and COMSOL numerical model were calculated for stainless steel 316 thin circular plates under room temperature conditions, where the fluid is water. The diameter of the circular plate is approximately one inch, and thickness is 10mil. Fluid flow velocity is in the range from 0.5m/s to 1m/s. The results from the two models are similar. Both the analytic model and COMSOL model showed that maximum stresses on the plate, which are at the radial boundary of the plate, are three orders of magnitude smaller than the yield strength and ultimate tensile strength. This indicates that the sensor is at a low risk of mechanical failure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Influence of Fuel Properties on Gasoline Direct Injection Particulate Matter Emissions Over First 200 s of World-Harmonized Light-Duty Test Procedure Using an Engine Dynamometer and Novel “Virtual Drivetrain” Software

Abstract The influence of fuel properties on particulate matter (PM) emissions from a catalytic gasoline particulate filter (GPF) equipped gasoline direct injection (GDI) engine was investigated using novel “virtual drivetrain” software and an engine mated to an engine dynamometer. The virtual drivetrain software was developed in labview to operate the engine on an engine dynamometer as if it were in a vehicle undergoing a driving cycle. The software uses a physics-based approach to determine vehicle acceleration and speed based on engine load and a programed “shift” schedule to control engine speed. The software uses a control algorithm to modulate engine load and braking to match a calculated vehicle speed with the prescribed speed trace of the driving cycle of choice. The first 200 s of the World-harmonized Light-duty Test Procedure (WLTP) driving cycle was tested using six different fuel formulations of varying volatility, aromaticity, and ethanol concentration. The first 200 s of the WLTP was chosen as the test condition because it is the most problematic section of the driving cycle for controlling PM emissions due to the cold start and cold drive off. It was found that there was a strong correlation between aromaticity of the fuel and the engine-out PM emissions, with the highest emitting fuel producing more than double the mass emissions of the low PM production fuel. However, the post-GPF PM emissions depended greatly on the soot loading state of the GPF. The fuel with the highest engine-out PM emissions produced comparable post-GPF emissions to the lowest PM producing fuel over the driving cycle when the GPF was loaded over three cycles with the respective fuels. These results demonstrate the importance of GPF loading state when aftertreatment systems are used for PM reduction. It also shows that GPF control may be more important than fuel properties, and that regulatory compliance for PM can be achieved with proper GPF control calibration irrespective of fuel type.

Energy & Fuels↗

thevenin: An Equivalent Circuit Modeling Package [SWR-24-132]

This package is a wrapper for the well-known Thevenin equivalent circuit model for simulating battery behavior with a focus on ease of use. The model is comprised of a single series resistor followed by any number of parallel RC pairs. The package includes an intuitive "experiment" interface, which simplifies the programming of constant or dynamic current, voltage, and/or power-driven loads, making it ideal for a wide range of applications, from basic tests to complex simulations. It also supports state-of-charge (SOC) and temperature-dependent properties, allowing the model to be more easily calibrated against real cells.

Randall, Corey↗

Identification of Final-State Neutrons in ANNIE

The Accelerator Neutrino Neutron Interaction Experiment (ANNIE) is a 26-ton gadolinium-loaded (Gd-loaded) water Cherenkov detector located on the Booster Neutrino beamline at Fermilab. ANNIE's primary physics objectives include measuring neutron multiplicity for neutrino-nucleus interactions and performing cross-section measurements of charge current quasi-elastic and neutral current quasi-elastic processes. These measurements aim to improve neutrino energy reconstruction and reduce uncertainties in current and future neutrino oscillation experiments. Additionally, ANNIE serves as a testbed for advanced technologies such as Large Area Picosecond Photodetectors (LAPPDs) and Water-Based Liquid Scintillator, which enhance vertex resolution and enable detection below the Cherenkov threshold. By leveraging the high neutron capture cross section of Gd-loaded water, ANNIE is well positioned to observe final-state neutrons in beam-correlated neutrino interactions. To constrain the uncertainties in the neutron capture efficiency and time within the detector, we have conducted multiple calibration campaigns using an AmBe source. The AmBe source is deployed at different locations of the tank to map the neutron capture efficiency and determine the expected neutron capture time. Additionally, the AmBe calibration data are used to define the precise neutron clustering that will be useful for identifying neutron-like clusters from neutrino interaction. In this poster, we will present the current status of the AmBe neutron calibration program and the development of neutron cluster definition for the ANNIE Experiment.

Ajana, Dhavalkumar [Florida State U.]↗

Dual-season thermal energy storage-integrated heat pump system for load shifting: experiments, modeling and nationwide analysis

Here, this paper proposes and validates a dual-season thermal energy storage-integrated heat pump (TES-HP) system that shifts building electric load in both cooling and heating modes using a single phase-change TES. The design uses the TES as a heat sink for the condenser in summer and a heat source for the evaporator in winter, thereby reducing on-peak electric demand while ensuring compatible with existing air-distribution systems. A 14-kW TES-HP prototype with six operating modes and novel refrigerant charge management strategies was experimentally tested under varied conditions. Subsequently, data-driven polynomial performance curves were developed and validated against experiments, then coupled with a phase change material (PCM) model and a calibrated building model within a rule-based controller. Single-day case studies demonstrated effective on-peak demand reduction while maintaining thermal comfort. During cooling, hourly power was lowered by up to 1.5 kW; in heating, average hourly power decreased from over 3.5 kW to 1.8 kW, compared to an HP-only system, achieving 64.5 % load shifting, and the need for resistance heating was eliminated. Seasonal simulations showed typical on-peak electricity savings of 25–35 % in cooling and 40–65 % in heating, with the largest benefits on the hottest and coldest days. Extended response-surface analysis and nationwide mapping quantified load shifting as functions of ambient and TES temperatures, revealing a seasonal trade-off in TES phase-change temperature. These results demonstrate the TES-HP system as a practical and scalable solution for grid-interactive buildings that reduces on-peak demand and electricity use while maintaining thermal comfort and enhancing grid flexibility and reliability.

Grid-interactive buildings↗