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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Application of thermal energy storage with electrified heating and cooling in a cold climate

Ground source heat pumps (GSHPs) have been shown to be an effective means of decarbonizing building heating and cooling, but the operation of these systems at scale presents challenges to sites and the grid due to increases in peak demand. Here, in this study, we investigate how the use of Thermal Energy Storage (TES), in the form of stratified water storage, could reduce the peak daily demand associated with GSHP systems and thus improve their cost effectiveness. This system was compared to a Combined Heat and Power (CHP) plant, to investigate the potential cost and emissions impacts of electrification on large energy users transitioning from high efficiency fossil fuel equipment. This study builds on previous research by using a significant campus area, and investigating the various impacts of an electrified system versus a state of the art fossil fuel system. An established method of TRNSYS modeling is used for the heat pumps and borehole heat exchangers (BHEs), along with the TES. The GSHP system with TES is modeled to follow industry standards and sized to provide an optimal balance of capital and operating costs. Costs were investigated for a unique large energy user rate structure, as well as for a more common generalized rate structure. The results show that the addition of TES to the GSHP system could reduce operating costs by 4.5%, but still incurs a 5.64% cost increase from the baseline CHP system. It is also shown, however, that a tactical integration of heat pumps into the CHP system is the most cost effective solution, only increasing the operating costs by 4.71%. Likewise, the impacts of different rate structures are highlighted, with the TES only resulting in 0.75% cost savings under the generalized utility rate. Furthermore, it is shown that thermal storage has great potential for demand reduction, with the addition of storage incurring a decrease of 7–22% in annual peak demand kW, dependent on the rate structure.

25 ENERGY STORAGE↗
DOE OSTI2025

Dampening of the Precipitation Response to Aerosol Pollution From Turbulence in Cumulus Clouds

Using aircraft observations and a cloud model with particle‐based microphysics, it is shown that the enhancement of drop collision‐coalescence from turbulence in clouds not only leads to earlier onset of rain in warm cumulus clouds as past studies have suggested, but also significantly dampens the precipitation susceptibility to aerosol loading. Enhanced drop coalescence from turbulence substantially increases the production of drizzle embryos just above cloud base, which in turn act as seeds that accelerate rain drop growth at mid and upper cloud levels even in highly polluted conditions. In contrast, pollution aerosols strongly inhibit rainfall when the commonly assumed gravitational‐only collision kernel is used and turbulent coalescence is neglected. Overall, turbulence‐enhanced drop coalescence strongly influences the response of warm cumulus clouds and precipitation to aerosol loading, suggesting that the effects of turbulent coalescence should be included in Earth system model representations of aerosol‐cloud‐precipitation interactions and aerosol indirect radiative forcing.

Chandrakar, Kamal Kant [NSF National Center for At↗
DOE OSTI2012

INL High Level Language Microcontroller Implementa

The overall goal of this project is to improve the security of embedded devices (microcontrollers) used in monitoring and control of energy-sector infrastructure. As these devices are essentially scaled-down personal computers (PCs), they are vulnerable to common low-level cyber-attacks such as buffer overflows and insecure authentication. The implementation of a modern high-level programming language on these microcontrollers would disallow such low-level attacks as the languages would have inherent safeguards against these types of cyber exploits. Idaho National Laboratory (INL) has partnered with Siemens Corporate Research (SCR) to develop and test a 4 th -generation language DNP3 implementation on real-world embedded hardware. These tests were carried out on control-system device models currently deployed in real-world applications. Testing was performed with existing C-based DNP implementation as well as the Python version developed by INL.

4GL↗
DOE OSTI2013

Assessment of Land Surface Model Performance in WRF for Simulating Wind at Heights Relevant to the Wind Energy Community

The Weather Research and Forecasting (WRF) model was used to investigate the impact of land surface model (LSM) physics on the simulated surface energy balance and the near surface wind profile, including heights reached by a modern wind turbine. Simulations were made for a domain centered over the Department of Energy (DOE) Southern Great Plains (SGP) Atmospheric Radiation Measurement Program (ARM) Central Facility in northern Oklahoma. High-resolution measurements of surface fluxes and profiles of wind speed, direction and turbulence were available for model validation. We tested 10 common LSM configurations in WRF including Noah, Noah-MP, SSiB, Pleim-Xiu, RUC, and others to evaluate (1) the accuracy of simulated surface energy fluxes, (2) the accuracy of forecasted rotor-disk height wind speeds, and (3) the sensitivity of rotor disk wind speed to the choice of LSM. WRF was run for four, two-week periods covering different canopy, surface meteorology and soil moisture conditions. LSM performances varied by simulation period and errors were greatest during periods with high soil moisture and live crop cover, indicating highest LSM sensitivity when PBL behavior is most coupled to land-atmosphere exchange. Higher wind speed errors also occurred at night during the spring, possibly from the difficulty with simulating nocturnal low-level jets. We found that choice of land surface model led to a ~10% improvement in simulating hub-height wind speed. Errors in wind shear were also sensitive to the choice of LSM. Overall the best performing models were Noah and Noah-MP. The variability of LSM performance across different soil moisture and vegetation canopy conditions suggests LSM representation of surface energy exchange processes in WRF remains a large source of model uncertainty. Furthermore, our results indicate the choice of LSM impacts simulated wind fields in WRF at heights relevant to the wind industry, at least for the Southern Great Plains region.

17 WIND ENERGY↗
DOE OSTI2017

An Open Source Extensible Smart Energy Framework

Aggregated distributed energy resources are the subject of much interest in the energy industry and are expected to play an important role in meeting our future energy needs by changing how we use, distribute and generate electricity. This energy future includes an increased amount of energy from renewable resources, load management techniques to improve resiliency and reliability, and distributed energy storage and generation capabilities that can be managed to meet the needs of the grid as well as individual customers. These energy assets are commonly referred to as Distributed Energy Resources (DER). DERs rely on a means to communicate information between an energy provider and multitudes of devices. Today DER control systems are typically vendor-specific, using custom hardware and software solutions. As a result, customers are locked into communication transport protocols, applications, tools, and data formats. Today’s systems are often difficult to extend to meet new application requirements, resulting in stranded assets when business requirements or energy management models evolve. By partnering with industry advisors and researchers, an implementation DER research platform was developed called the Smart Energy Framework (SEF). The hypothesis of this research was that an open source Internet of Things (IoT) framework could play a role in creating a commodity-based eco-system for DER assets that would reduce costs and provide interoperable products. SEF is based on the AllJoynTM IoT open source framework. The demonstration system incorporated DER assets, specifically batteries and smart water heaters. To verify the behavior of the distributed system, models of water heaters and batteries were also developed. An IoT interface for communicating between the assets and a control server was defined. This interface supports a series of “events” and telemetry reporting, similar to those defined by current smart grid communication standards. The results of this effort demonstrated the feasibility and application potential of using IoT frameworks for the creation of commodity-based DER systems. All of the identified commodity-based system requirements were met by the AllJoyn framework. By having commodity solutions, small vendors can enter the market and the cost of implementation for all parties is reduced. Utilities and aggregators can choose from multiple interoperable products reducing the risk of stranded assets. Based on this research it is recommended that interfaces based on existing smart grid communication protocol standards be created for these emerging IoT frameworks. These interfaces should be standardized as part of the IoT framework allowing for interoperability testing and certification. Similarly, IoT frameworks are introducing application level security. This type of security is needed for protecting application and platforms and will be important moving forward. Recommendations are that along with DER-based data model interfaces, platform and application security requirements also be prescribed when IoT devices support DER applications.

25 ENERGY STORAGE↗
DOE OSTI2021

Modeling Framework for Evaluating Grid Disturbances

Recent research in the literature proposed parameter-based functional forms to quantify the impact of disturbances on electric power grids. This modeling was based on a concept of generalized grid disturbances that harmonized reliability and resilience. Three main stages—avoid, react, and recover—were identified, and to support practicality, were intended to be independently planned. An objective of the grid disturbance model was to fairly analyze the potential impacts of novel mitigations like transactive energy systems (TES) on grid reliability and resilience. Quantitative evaluation of a common performance metric (e.g., area under the curve of percentage customers online before, during, and after an event) over time was shown as an effective tool for such analysis. Such quantification may also enable system planners to assess the impact of appropriate mitigative actions for improving grid performance against potential disturbances. This is the focus of this report, i.e., presenting an evaluation modeling framework that can be utilized to evaluate grid performance against disturbances, under a variety of existing and possible new mitigative actions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Gene network centrality analysis identifies key regulators coordinating day-night metabolic transitions in Synechococcus elongatus PCC 7942 despite limited accuracy in predicting direct regulator-gene interactions

Synechococcus elongatus PCC 7942 is a model organism for studying circadian regulation and bioproduction, where precise temporal control of metabolism significantly impacts photosynthetic efficiency and CO 2 -to-bioproduct conversion. Despite extensive research on core clock components, our understanding of the broader regulatory network orchestrating genome-wide metabolic transitions remains incomplete. We address this gap by applying machine learning tools and network analysis to investigate the transcriptional architecture governing circadian-controlled gene expression. While our approach showed moderate accuracy in predicting individual transcription factor-gene interactions - a common challenge with real expression data - network-level topological analysis successfully revealed the organizational principles of circadian regulation. Our analysis identified distinct regulatory modules coordinating day-night metabolic transitions, with photosynthesis and carbon/nitrogen metabolism controlled by day-phase regulators, while nighttime modules orchestrate glycogen mobilization and redox metabolism. Through network centrality analysis, we identified potentially significant but previously understudied transcriptional regulators: HimA as a putative DNA architecture regulator, and TetR and SrrB as potential coordinators of nighttime metabolism, working alongside established global regulators RpaA and RpaB. This work demonstrates how network-level analysis can extract biologically meaningful insights despite limitations in predicting direct regulatory interactions. The regulatory principles uncovered here advance our understanding of how cyanobacteria coordinate complex metabolic transitions and may inform metabolic engineering strategies for enhanced photosynthetic bioproduction from CO 2 .

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

TIE02. IGARSS’2024 Townhall on “Digital Twins for Earth Science

NASA, ESA, NOAA, CNES and several other international organizations have started programs to design and develop Digital Twins of the Earth and/or Earth systems. Earth Systems Digital Twins (ESDTs) are dynamic and interactive information systems for understanding, forecasting, and conjecturing the complex interconnections among Earth systems, including anthropomorphic forcings and impacts to humanity. Organized around interconnected, multi-domain, high-scale modeling capabilities, the three major components of an Earth System Digital Twin are a continuously updated Digital Replica of the Earth System of interest (or “What Now”), dynamic Forecasting models (or “What Next”), and Impact Assessment capabilities (or “What If”). ESDTs provide unified, comprehensive representations and predictions that can be utilized for monitoring the health of the Planet, as well as for developing actionable information to support decision making. More generally, Digital Twins will help researchers better understand the fundamental Earth systems that impact everything from wildfires to climate change. This Townhall will provide a status of Destination Earth as well as ESA’s, NASA’s, CNES’s and NOAA’s current independent and common efforts in Digital Twins; then the four organizations will provide information about community building before engaging a dialogue about Digital Twins of the Earth with the IGARSS community.

Earth Science Remote Sensing; Information Systems;↗
DOE OSTI2024

New systems in MOOSE

The Multiphysics Object-Oriented Simulation Environment (MOOSE) serves as a common library of classes between applications developed for advanced reactor analysis, fusion device engineering, spent fuel cask analysis, geochemistry studies, among other fields. These applications drive the development of the framework to meet their needs. Systems in MOOSE group capabilities that share a common purpose and generally common code. They can be leveraged by all downstream applications, providing extensive code re-use and shared maintenance. They facilitate the discovery by new users of the classes meeting at least partially their needs, and offer the same opportunities for customization as other systems. The addition of a new system to MOOSE opens new ways of solving or discretizing nonlinear problems, of performing distributed postprocessing, and a plethora of other needs. While new systems can be introduced in downstream applications rather than at the framework level, the framework team monitors common needs across the community and often triggers their addition. Documentation, training material, development needs can be centralized, limiting duplicated work across the community. The last three years have seen a large expansion in the capabilities of MOOSE. The supporting role of the framework in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has created numerous feature requests to support neutronics, thermal hydraulics, computational fluid dynamics and thermo-mechanics simulations in the Griffin, SAM, Pronghorn and Bison applications respectively. Similarly, laboratory-directed research and development (LDRD) projects in additive manufacturing, high-Reynolds flow simulations, structure optimization also necessitate an expansion of the framework capabilities. This summary reports on the new systems created in MOOSE, their design, their capabilities and some of the relevant interfaces.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Morse-Smale Analysis of Ion Diffusion in Ab Initio Battery Materials Simulations

Ab initio molecular dynamics (AIMD) simulations are increasingly useful in modeling, optimizing and synthesizing materials in energy sciences. In solving Schrödinger’s equation, they generate the electronic structure of the simulated atoms as a scalar field. However, methods for analyzing these volume data are not yet common in molecular visualization. The Morse-Smale complex is a proven, versatile tool for topological analysis of scalar fields. In this paper, we apply the discrete Morse-Smale complex to analysis of first-principles battery materials simulations. We consider a carbon nanosphere structure used in battery materials research, and employ Morse-Smale decomposition to determine the possible lithium ion diffusion paths within that structure. Our approach is novel in that it uses the wavefunction itself as opposed distance fields, and that we analyze the 1-skeleton of the Morse-Smale complex to reconstruct our diffusion paths. Furthermore, it is the first application where specific motifs in the graph structure of the complete 1-skeleton define features, namely carbon rings with specific valence. We compare our analysis of DFT data with that of a distance field approximation, and discuss implications on larger classical molecular dynamics simulations.

25 ENERGY STORAGE↗
DOE OSTI2014

Deposition Velocity Methods For DOE Site Safety Analyses

This report documents the results of an investigation of deposition velocity methods for use in Department of Energy (DOE) Documented Safety Analysis (DSA) modeling. The project was sponsored by the National Nuclear Security Administration (NNSA) Nuclear Safety Research and Development Program and monitored by the Chief of Nuclear Safety (CNS) from the Office of the Under Secretary for Management and Performance. Based on initial scoping discussions, the primary focus of this effort was on the dry deposition of particulate matter. However, within the constraints of the project, we also explored the sensitivity of safety analysis modeling to other key input parameters (wind direction variability, atmospheric stability, release characteristics, model assumptions), examined the 95 th percentile methodology, and investigated a few aspects of a commonly-used DOE safety analysis code, MACCS2 (MELCOR Accident Consequence Code System).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Stand Alone Battery Thermal Management System

The objective of this project is research, development and demonstration of innovative thermal management concepts that reduce the cell or battery weight, complexity (component count) and/or cost by at least 20%. The project addresses two issues that are common problems with current state of the art lithium ion battery packs used in vehicles; low power at cold temperatures and reduced battery life when exposed to high temperatures. Typically, battery packs are “oversized” to satisfy the two issues mentioned above. The first phase of the project was spent making a battery pack simulation model using AMEsim software. The battery pack used as a benchmark was from the Fiat 500EV. FCA and NREL provided vehicle data and cell data that allowed an accurate model to be created that matched the electrical and thermal characteristics of the actual battery pack. The second phase involved using the battery model from the first phase and evaluate different thermal management concepts. In the end, a gas injection heat pump system was chosen as the dedicated thermal system to both heat and cool the battery pack. Based on the simulation model. The heat pump system could use 50% less energy to heat the battery pack in -20°C ambient conditions, and by keeping the battery cooler at hot climates, the battery pack size could be reduced by 5% and still meet the warranty requirements. During the final phase, the actual battery pack and heat pump system were installed in a test bench at DENSO to validate the simulation results. Also during this phase, the system was moved to NREL where testing was also done to validate the results. In conclusion, the heat pump system can improve “fuel economy” (for electric vehicle) by 12% average in cold climates. Also, the battery pack size, or capacity, could be reduced 5%, or if pack size is kept constant, the pack life could be increased by two years. Finally, the total battery pack and thermal system cost could be reduced 5% only if the system is integrated with the vehicle cabin air conditioning system. The reason why we were not able to achieve the 20% reduction target is because of the natural decay of the battery cell due to the number of cycles. Perhaps newer battery chemistries that are not so sensitive to cycling would have more potential for reducing the battery size due to thermal issues.

25 ENERGY STORAGE↗
DOE OSTI2018

Advanced Models for Nondestructive Evaluation of Aging Nuclear Power Plant Cables

Background: Nuclear power plant (NPP) cables must function correctly for proper power supply and control of the nuclear reactor. This is especially important for public and environmental safety at critical times such as during reactor shut-down following loss of coolant. Over extended periods of service, the cable insulation and jacket polymer materials suffer from degradation due to exposure to environmental stressors such as heat and ionizing radiation. The focus of this project has been the development of detailed descriptions of the way in which insulation polymers degrade, from a materials science perspective, and the development of new electrical techniques to monitor cable polymer condition nondestructively. Objectives: The objectives of this project have been to i) perform detailed characterization experiments upon cable insulation polymers that have experienced thermal and radiation exposure mimicking that received during NPP operation, including the exploration of novel cable nondestructive evaluation methods; capacitive, THz and infrared methods; ii) identify the most sensitive indicators of aging in these materials, and iii) develop advanced, validated models describing microstructural and chemical changes that are observed in cable insulation polymers due to thermal and radiation exposure. Methods: Accelerated aging was performed on the two most common United States NPP cable insulation polymers (cross-linked polyethylene (XLPE) and ethylene propylene rubber (EPR)) under various conditions of elevated temperature and gamma radiation dose. Aging mechanisms were elucidated through extensive thermal, mechanical and microscopic characterization of the aged samples, and materials modeling. Dielectric and IR spectra were measured on pristine and aged samples. Data was analyzed statistically, via multiple linear regression, partial least squares and probabilistic neural network approaches. Impact: Extant cable monitoring techniques do not deal successfully with all polymer types. This research has laid a foundation upon which new electrical nondestructive test methods for cable polymer condition monitoring may be developed, hence launching the development of new test methods for cable insulation monitoring based on measuring electrical rather than mechanical parameters. Collaboration: This project has benefitted from collaboration between experts in materials science and engineering, materials modeling, electrical engineering, and nondestructive evaluation. The majority of the characterization measurements were carried out at Iowa State University. Materials modeling was carried out primarily at Washington State University. Irradiation of samples took place at Pacific Northwest National Laboratory (PNNL), where a student intern from Iowa State was hosted for one summer, setting up the aging experiments. A research student from the University of Bologna, Italy, joined the project for their thesis research at Iowa State University with samples provided by PNNL. The project benefitted from regular involvement of senior engineers in US-based industry partners. Project investigators presented findings at various national and international conferences and workshops.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Baylor University Campus-Wide Deep Dive

In January 2020, staff members from the Engagement and Performance Operations Center (EPOC) and the Lonestar Education And Research Network (LEARN) met with researchers and staff at Baylor University for the purpose of a Campus-Wide Deep Dive into research drivers. The goal of this meeting was to help characterize the requirements for five campus research use cases and to enable cyberinfrastructure support staff to better understand the needs of the researchers they support. Profiled scientific use cases included: - Experimental High Energy Physics (HEP) - Proton Computed Tomography (pCT) - Nutrition and Relation to Digestive Microbiome - Baylor University Core Research Facilities - Molecular Quantum-dot Cellular Automata (QCA), and Material Science of Quantum Computing - Modeling and Simulation of Low-Dimensional and Nano-Structured Materials - Computational Fluid Dynamics Material for this event included the written documentation from each of the research areas at Baylor University, documentation about the current state of technology support, and a write-up of the discussion that took place in person. The Case Studies highlighted the ongoing challenges that Baylor University has in supporting a cross-section of established and emerging research use cases. Each Case Study mentioned unique challenges which were summarized into common needs. These included: - Tradeoffs for network/software security, and usability of the resulting infrastructure. Better communication to set expectations and understand realities is required. - Computation use on campus is widespread and healthy. While no major problems were uncovered, upgrades to maintain current usage patterns and encourage growth will be required. - Storage is a critical need for enterprise use cases and research. In particular, a campus wide ‘storage architecture’ to support research use cases (e.g. instruments, data sharing) is required in the 2-5 year time window. - Instrumentation on campus is healthy and expanding. Technology must scale with this in the form of computation and storage. - Working with LEARN to upgrade network capacity (in multiples of 10G, or upgrades to 100G) will be required in the 1-3 year time frame. - Network monitoring and visibility will help to establish external science use cases. - Data sharing via portal systems is not currently a critical need, but growing in scope. EPOC can assist Baylor with options.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2003

Atomic Oxygen Durability of Aluminized Polymers

The atomic oxygen durability of aluminized polymers will be investigated. Such aluminized polymers are commonly used in space and specifically on the International Space Station. Recent data from in-space results indicates that vapor deposited aluminum coatings are highly defected with many small pin windows. However, electron microscopy to validate the size and aerial density of such defects remains to be demonstrated. The research project is planned to compare electron microscopy analysis of pristine and atomic oxygen exposed aluminized polyimide Kapton with the results of ground laboratory atomic oxygen erosion data, in-space results and computational Monte Carlo modeling to develop a self consistent understanding of the atomic oxygen degradation processes and effects.

Yang, Judith C.↗
NASA NTRS2019

Solid Fuel Ignition and Extinction (SoFIE) Project on ISS

The Solid Fuel Ignition and Extinction (SoFIE) project studies ignition and flammability of solid spacecraft materials (fuels) in practical geometries and realistic atmospheric conditions. It is an experiment insert designed for use within the existing Combustion Integrated Rack (CIR). The CIR chamber provides a level of containment and permits testing at variable oxygen concentrations and pressures representative of current and planned NASA Space Exploration Atmospheres. The applications of SoFIE include: (1) Determining safer selection of cabin materials and validating NASA materials flammability selection using 1-g test protocols for low-gravity fires, (2) Improving understanding of early fire growth behavior, (3) Validating material flammability numerical models, (4) Determining optimal suppression techniques for burning materials by diluents, flow reduction, and venting, (5) Obtaining burning behavior of actual engineering materials planned for spacecraft, (6) Developing corresponding models of microgravity flame spread, flammability, and extinction, and use the results to improve normal gravity combustion models for terrestrial applications. The hardware permits a wide range of solid-material combustion and fire suppression studies. It supports multiple investigations using common infrastructure including sample holders, flow control, test sections, external radiant heaters, igniters, and diagnostics. SoFIE has been developed to meet the requirements of five unique investigations. It is currently being built and slated to begin operations on the ISS in July 2021. Given the general capabilities of the hardware insert, it is intended to be used as a facility for future researchers who can propose to NASA for related solid combustion studies.

Ferkul, Paul↗
DOE OSTI2015

LESSONS FROM NUCLEAR ENERGY: BUILDING SNOW AND AVALANCHE SIMULATION TOOLS USING A COMMON OPEN-SOURCE FRAMEWORK

The Department of Energy (DOE) is currently investing millions of dollars annually into various modeling and simulation tools for all aspects of nuclear energy. An important part of this effort includes developing applications based on the open-source Multiphysics Object Oriented Simulation Environment (MOOSE; mooseframework.org) from Idaho National Laboratory (INL). Through the DOE and outside collaborators, MOOSE includes a large set of physics modules, including phase field, level set, heat conduction, tensor mechanics, Navier-Stokes, and porous media, among others. The phase-field module, in particular, is well-suited for micro-structure evolution simulations, including solidification, as shown in the figure. It was also used, in conjunction with the heat conduction module, to build a multiscale snow model (Pika) as presented at the 2014 International Snow Science Workshop (Slaughter et al., 2014). The snow science community should learn from the nuclear industry, and harness the enormous effort underway to build simulation tools that are open, modular, and share a common framework. In particular, MOOSE-based multi-physics solvers are inherently parallel, dimension agnostic, adaptive in time and space, fully-coupled, and capable of interacting with other applications. The snow science community must build on existing tools to enable collaboration between researchers and practitioners throughout the world, and advance the state-of-the-art in line with other scientific research efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

An Adaptive Dynamic Agrivoltaic Production Tool

In the pursuit of sustainable and land-use-efficient solutions to mitigate climate change, the concept of agrivoltaic systems, which integrate renewable solar energy into conventional agriculture, has emerged. By deploying solar arrays above the crop field, these systems are designed to maximize the land use efficiency or, in other words, the value of generated electricity and crop yield per unit area. While power generation has been extensively studied and modeled, research gaps persist in simulating crop performance [1], [2]. Early studies utilized generalized relationships between photosynthetically active radiation (PAR) and crop production. However, significant variations in crop performance due to other factors, such as weather and soil, can compromise the reliability of the results [2]. Current studies focus on comprehensive process-based crop models, such as DSSAT [3] and STICS [4]. Nevertheless, the validation status varies greatly across different species, and the validation process requires well-designed experiments to adjust specific processes. For less common shade-tolerant crops with limited validation, such as cabbage, physiological behaviors can be difficult to predict [5]. This study investigates an adaptive dynamic agrivoltaic production tool (ADAPT) with few data requirements and minimal on-site calibration that can be easily applied in real applications.

Long, Qirui↗