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NASA's Ares I and Ares V Launch Vehicles -- Effective Space Operations Through Efficient Ground Operations

The United States (U.S.) plans to return to the Moon by 2020, with the development of a new human-rated space transportation system to replace the Space Shuttle, which is due for retirement in 2010 after it completes its missions of building the International Space Station and servicing the Hubble Space Telescope. Powering the future of space-based scientific exploration will be the Ares I Crew Launch Vehicle, which will transport the Orion Crew Exploration Vehicle to orbit where it will rendezvous with the Lunar Lander. which will be delivered by the Ares V Cargo Launch Vehicle. This new transportation infrastructure, developed by the National Aeronautics and Space Administration (NASA), will allow astronauts to leave low-Earth orbit for extended lunar exploration and preparation for the first footprint on Mars. All space-based operations begin and are controlled from Earth. NASA's philosophy is to deliver safe, reliable, and cost-effective solutions to sustain a multi-billion-dollar program across several decades. Leveraging 50 years of lessons learned, NASA is partnering with private industry, while building on proven hardware experience. This paper will discuss how the Engineering Directorate at NASA's Marshall Space Flight Center is working with the Ares Projects Office to streamline ground operations concepts and reduce costs. Currently, NASA's budget is around $17 billion, which is less than 1 percent of the U.S. Federal budget. Of this amount, NASA invests approximately $4.5 billion each year in Space Shuttle operations, regardless of whether the spacecraft is flying or not. The affordability requirement is for the Ares I to reduce this expense by 50 percent, in order to allow NASA to invest more in space-based scientific operations. Focusing on this metric, the Engineering Directorate provides several solutions-oriented approaches, including Lean/Six Sigma practices and streamlined hardware testing and integration, such as assembling major hardware elements before shipping to the Kennedy Space Center for launch operations. This paper provides top-level details for several cost saving initiatives, including both process and product improvements that will result in space transportation systems that are designed with operations efficiencies in mind. The Engineering Directorate provides both the intellectual capital embodied in an experienced workforce and unique facilities in which to validate the information technology tools that allow a nationwide team to collaboratively connect across miles that separate them and the engineering disciplines that integrate various piece parts into a whole system. As NASA transforms ground-based operations, it also is transitioning its workforce from an era of intense hands-on labor to a new one of mechanized conveniences and robust hardware with simpler interfaces. Ensuring that space exploration is on sound footing requires that operations efficiencies be designed into the transportation system and implemented in the development stage. Applying experience gained through decades of ground and space op'erations, while using value-added processes and modern business and engineering tools, is the philosophy upon which a new era of exploration will be built to solve some of the most pressing exploration challenges today -- namely, safety, reliability, and affordability.

Dumbacher, Daniel L.

Use of Remote Sensing Data to Enhance NWS Storm Damage Toolkit

In the wake of a natural disaster such as a tornado, the National Weather Service (NWS) is required to provide a very detailed and timely storm damage assessment to local, state and federal homeland security officials. The Post ]Storm Data Acquisition (PSDA) procedure involves the acquisition and assembly of highly perishable data necessary for accurate post ]event analysis and potential integration into a geographic information system (GIS) available to its end users and associated decision makers. Information gained from the process also enables the NWS to increase its knowledge of extreme events, learn how to better use existing equipment, improve NWS warning programs, and provide accurate storm intensity and damage information to the news media and academia. To help collect and manage all of this information, forecasters in NWS Southern Region are currently developing a Storm Damage Assessment Toolkit (SDAT), which incorporates GIS ]capable phones and laptops into the PSDA process by tagging damage photography, location, and storm damage details with GPS coordinates for aggregation within the GIS database. However, this tool alone does not fully integrate radar and ground based storm damage reports nor does it help to identify undetected storm damage regions. In many cases, information on storm damage location (beginning and ending points, swath width, etc.) from ground surveys is incomplete or difficult to obtain. Geographic factors (terrain and limited roads in rural areas), manpower limitations, and other logistical constraints often prevent the gathering of a comprehensive picture of tornado or hail damage, and may allow damage regions to go undetected. Molthan et al. (2011) have shown that high resolution satellite data can provide additional valuable information on storm damage tracks to augment this database. This paper presents initial development to integrate satellitederived damage track information into the SDAT for near real ]time use by forecasters and decision makers.

Jedlove, Gary J.

(abstract) Student Involvement in the Pluto Mission

The Pluto Fast Flyby mission development baseline consists of 2 identical spacecraft (120 - 165 kg) to be launched to Pluto/ Charon in the late 1990s. These spacecraft are intended to fly by Pluto and Charon in order to perform various remote-sensing scientific investigations and have a mission development cost less than $400M (FY92$) through launch plus 30 days. The Pluto team is committed to involving students in all areas of mission development and operations. In November 1992, the Pluto team sent a request for information to industry and universities looking for ways to lower the mass and cost of the mission. A number of universities responded with creative and promising technological developments. In addition to contracts with industry and other federal labs, contracts were signed with schools which allowed students to apply their research, enabling the Pluto team to use valuable resources on a variety of advanced technology endeavors. Perhaps the most exciting aspect of these investigations was that the deliverables that the students produced were not just final reports, but actual prototype hardware complete with write-ups on lessons learned in machining, programming, and design. Another exciting development was a prototype adapter competition in which 7 universities competed to design, build, and test their idea of a lightweight spacecraft-propulsion stack adapter. Georgia Tech won with an innovative dodecahedron composite lattice cone. Other students from other universities were involved as well. All in all, over 40 students from 20 different colleges made significant contributions to the Pluto Fast Flyby mission development through their efforts. This paper will give an overview of Pluto student involvement, the technologies which they examined, and useful results for the mission.

Pluto student involvement design universities tech

A Survey of Current Rotorcraft Propulsion Health Monitoring Technologies

A brief review is presented on the state-of-the-art in rotorcraft engine health monitoring technologies including summaries on current practices in the area of sensors, data acquisition, monitoring and analysis. Also, presented are guidelines for verification and validation of Health Usage Monitoring System (HUMS) and specifically for maintenance credits to extend part life. Finally, a number of new efforts in HUMS are summarized as well as lessons learned and future challenges. In particular, gaps are identified to supporting maintenance credits to extend rotorcraft engine part life. A number of data sources were consulted and include results from a survey from the HUMS community, Society of Automotive Engineers (SAE) documents, American Helicopter Society (AHS) papers, as well as references from Defence Science & Technology Organization (DSTO), Civil Aviation Authority (CAA), and Federal Aviation Administration (FAA).

Delgado, Irebert R.

Introduction

The 2014 SPIE Sensing Technologies for Global Health, Military Medicine and Environmental Monitoring conference embraced a wealth of state-of-the-art information in basic and applied science. This event covered the latest developments in the following areas: Non-invasive Disease Diagnostics for Global Health- This opening series of two consecutive sessions focused on oral biospecimen based rapid assays and point-of-care devices for the detection of pathogens causing infectious diseases, biomarkers for cancer, and analytes for noncommunicable diseases such as diabetes. They also covered presentations on the human proteasome and microbiome with linkage to human diseases and diagnostic approaches. The sessions were built on the past experience and expertise of the National Institutes of Health, National Institutes of Dental and Craniofacial Research. Military Medicine I: Traumatic Brain Injury and PTSD-This assembly covered oral-biomarker based diagnostics for brain damage and TBI as well as prevention and rehabilitation technologies. Neurorehabilitation and noninvasive neuromodulation were also discussed as critical approaches for effective functioning. Military Medicine II: Physiology and Medicine of Extreme Environments and Spaceflight-This scientific segment showcased physiological, pharmacological and diagnostic sensing methodologies during spaceflight per the National Aeronautics and Space Administration as well as military-relevant toxicans and future sensing trends per the Department of Defense. It also included latest technologies to determine hydration status in warfighters, eye surgery using the latest laser technologies, and sensing tools for blood analysis.  Sensing Technologies for Disease Diagnostics and Environmental Monitoring-This closing series of two consecutive sessions provided the venues to learn and discuss more results on the next generation of diagnostic tools and field technologies for diseases, including biomarker detection by digital imaging, multiplex technologies, capillary electrophoresis and molecular platforms serving as labs-on-chips. This conference allowed cross-fertilization of ideas, projects and collaborative work by a multidisciplinary audience of national and international colleagues from the academia, industry and federal government: The National Institutes of Health, National Aeronautics and Space Administration, and the Department of Defense.

Wotring, Virginia E.

Pathways and Challenges to Innovation in Aerospace

This paper explores impediments to innovation in aerospace and suggests how successful pathways from other industries can be adopted to facilitate greater innovation. Because of its nature, space exploration would seem to be a ripe field of technical innovation. However, engineering can also be a frustratingly conservative endeavor when the realities of cost and risk are included. Impediments like the "find the fault" engineering culture, the treatment of technical risk as almost always evaluated in terms of negative impact, the difficult to account for expansive Moore's Law growth when making predictions, and the stove-piped structural organization of most large aerospace companies and federally funded research laboratories tend to inhibit cross-cutting technical innovation. One successful example of a multi-use cross cutting application that can scale with Moore's Law is the Evolutionary Computational Methods (ECM) technique developed at the Jet Propulsion Lab for automated spectral retrieval. Future innovations like computational engineering and automated design optimization can potentially redefine space exploration, but will require learning lessons from successful innovators.

Terrile, Richard J.

Automated Mapping of Flood Events in the Mississippi River Basin Utilizing NASA Earth Observations

The Mississippi River Basin is the fourth largest drainage basin in the world, and is susceptible to multi-level flood events caused by heavy precipitation, snow melt, and changes in water table levels. Conducting flood analysis during periods of disaster is a challenging endeavor for NASA's Short-term Prediction Research and Transition Center (SPoRT), Federal Emergency Management Agency (FEMA), and the U.S. Geological Survey's Hazards Data Distribution Systems (USGS HDDS) due to heavily-involved research and lack of manpower. During this project, an automated script was generated that performs high-level flood analysis to relieve the workload for end-users. The script incorporated Landsat 8 Operational Land Imager (OLI) tiles and utilized computer-learning techniques to generate accurate water extent maps. The script referenced the Moderate Resolution Imaging Spectroradiometer (MODIS) land-water mask to isolate areas of flood induced waters. These areas were overlaid onto the National Land Cover Database's (NLCD) land cover data, the Oak Ridge National Laboratory's LandScan data, and Homeland Infrastructure Foundation-Level Data (HIFLD) to determine the classification of areas impacted and the population density affected by flooding. The automated algorithm was initially tested on the September 2016 flood event that occurred in Upper Mississippi River Basin, and was then further tested on multiple flood events within the Mississippi River Basin. This script allows end users to create their own flood probability and impact maps for disaster mitigation and recovery efforts.

Bartkovich, Mercedes

NASA GeneLab: Open Science for Life in Space

NASA’s GeneLab helps scientists understand how the fundamental building blocks of life – DNA, RNA, proteins, and metabolites – change from exposure to the space environment including microgravity and cosmic radiation exposure. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data (collectively known as omics data) alongside essential metadata describing each spaceflight and space-relevant experiment. The open-access GeneLab repository currently consists of over 300 omics datasets generated by biological experiments, involving various model organisms, that are relevant to spaceflight. In order to maximize the intelligibility of these data, particularly for users with limited bioinformatics knowledge, GeneLab has started processing and analyzing these datasets to generate differential gene expression data and identify biological and physiological pathways that are dysregulated as a result of spaceflight. To aide GeneLab’s efforts to harmonize and democratize space-relevant omics data, over 130 scientists have joined one of four GeneLab Analysis Working Groups (Animal AWG, Plant AWG, Microbe AWG, Multi-Omics AWG) and together helped develop and adopted standard data analysis workflows for all data types available in GeneLab. Currently, the GeneLab Data System includes a data repository with federated search capability, an online controlled-access toolshed powered by "Galaxy" for users to process data with vetted standard workflows, a workspace for data sharing, a data submission portal, and the ability to browse and visualize transcriptomics processed data. The user interface was designed to be accessible to a broad variety of users, including high school and college students who can use it to learn about omics data analysis and space biology. The visualization portal enhances GeneLab’s ability to democratize omics data by removing the need for bioinformatics expertise to interpret transcriptomics data hosted on GeneLab. This presentation will provide an over-view of NASA’s GeneLab including how to navigate the GeneLab Data System and will conclude by providing resources for opportunities to work with GeneLab and NASA at large.

Amanda M Saravia-Butler

Definition and Demonstration of a Methodology for Validating Aircraft Trajectory Predictors

This paper presents a new methodology for validating an aircraft trajectory predictor, inspired by the lessons learned from a number of field trials, flight tests and simulation experiments for the development of trajectory-predictor-based automation. The methodology introduces new techniques and a new multi-staged approach to reduce the effort in identifying and resolving validation failures, avoiding the potentially large costs associated with failures during a single-stage, pass/fail approach. As a case study, the validation effort performed by the Federal Aviation Administration for its En Route Automation Modernization (ERAM) system is analyzed to illustrate the real-world applicability of this methodology. During this validation effort, ERAM initially failed to achieve six of its eight requirements associated with trajectory prediction and conflict probe. The ERAM validation issues have since been addressed, but to illustrate how the methodology could have benefited the FAA effort, additional techniques are presented that could have been used to resolve some of these issues. Using data from the ERAM validation effort, it is demonstrated that these new techniques could have identified trajectory prediction error sources that contributed to several of the unmet ERAM requirements.

Vivona, Robert A.

Building Capacity to Use Earth Observations for Land Monitoring: A Synoptic Review of NASA DEVELOP’s Terrestrial Projects

The NASA DEVELOP Program addresses environmental and public policy issues through interdisciplinary research studies that apply the lens of Earth observations to decision making. The program builds capacity in both programmatic participants (e.g., students and recent graduates) and partner organizations (e.g., federal agencies and non-governmental organizations) to use and integrate Earth science information into environmental decision making. DEVELOP conducts 50-60 projects each year, with approximately three quarters of projects focusing on terrestrial-related topics such as monitoring and assessing land use/land change, vegetation health, agriculture, water resources, and urban development. This presentation will share the DEVELOP model for building capacity, highlight example project case studies, and share lessons learned working with a wide variety of partner organizations.

Capacity Building

NASA’s Global Precipitation Measurement Mission: Leveraging Stakeholder Engagement & Applications Activities to Inform Decision-making

The application of satellite precipitation estimates from NASA’s Global Precipitation Measurement (GPM) Mission for decision-making has been a focus for the mission since launch. As a result, GPM data have enabled a range of applications that address societal needs, including water resource management, crop forecasting, ecological monitoring, disaster response, public health, aviation, weather forecasting, and climate modeling, among others. GPM applications activities have continued to focus on user engagement through in person trainings and interviews, workshops, webinars, and educational outreach activities. The goals of these efforts are to synthesize community data needs in order to effectively support and enable decision-making across agencies, academia and the global community. While these efforts have helped the GPM mission establish a large stakeholder community that encompasses federal and state partners, academic institutions, nd private and nonprofit companies, there remains difficulties associated with accessing, processing, and applying the data to support or enable applications. In this article, we present GPM applications strategies and approaches used to enhance the applications value of GPM data, and most importantly, demonstrate how these efforts have and can inform different decision-making contexts. This work also provides a discussion on key lessons learned from the user community and how this information can be utilized to help better support and shape applications approaches for future NASA Earth Science missions.

Satellite precipitation

2020 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is essential for addressing the increasingly complex national workforce demands stemming from the growth of computational science and engineering challenges. Computational science and engineering (CSE) takes a multidisciplinary approach that utilizes scientific computing to tackle practical problems and provide technical tools across the spectrum of scientific discovery. The DOE CSGF specifically highlights high-performance computing (HPC) as a critical enabling technology in CSE, driving advancements in science and engineering that are vital to both the DOE and the broader economy. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines have been transformed through the augmentation of scientific observation via HPC. At government laboratories, academic institutions, and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, quantum information systems, fusion-reactor design, machine learning, additive manufacturing, nano materials for next-generation batteries and transistors, and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing. Computational biology, machine learning, and quantum computing are among the subjects that began to swell in the ranks of CSGF applicants before the labs were hiring as high a percentage of employees in these categories.” The explosion of scientific and technological data has heightened the demand for advanced high-performance computing (HPC) to transform these data into meaningful scientific insights. As access to vast amounts of data increases, the fields of Machine Learning and Artificial Intelligence are experiencing a resurgence, enhancing the established practices of computational modeling and simulation. In its September 2020 subcommittee report on "AI/ML, Data Intensive Science, and High-Performance Computing," the DOE Advanced Scientific Computing Advisory Committee (ASCAC) specifically called for a fellowship program to train computational and data scientists to address exascale and data-intensive computing challenges. This integration of empirical and theoretical modeling will increasingly guide federal policymakers in making decisions that impact American society and future generations. It demands a workforce of highly skilled and intellectually agile computational scientists capable of navigating the rapid advancements in scientific computing within the DOE National Laboratory research environment. The DOE CSGF program has consistently addressed this critical need.

97 MATHEMATICS AND COMPUTING

Manufacturing Full-Scale High Gradient Copper Accelerators: Electron Beam Welding and Allied Processes

This DOE ARDAP-funded study examines the technical and business feasibility of manufacturing high-gradient normal conducting RF (NCRF) copper accelerating structures using electron beam welding (EBW) instead of conventional high-temperature brazing. The core motivation is material performance: brazing softens copper significantly, while hard copper alloys have demonstrated ~75% higher operational gradients in SLAC tests, making cold-joining techniques highly attractive. EBW, applied to split-cell (half or quadrant) structure designs, preserves copper hardness away from the weld joint and simplifies machining — but industrial process optimization remains immature and a substantial learning curve is expected. The business case was modeled for two scenarios: a greenfield EBW linac company (> $10M upfront costs, viable above ~30 units/year) and an EBW division added to an existing accelerator firm to reduce risk and upfront costs, at the expense of being less optimal structure for the higher volume production. The study concludes that without a significant increase in demand, private investment alone cannot sustain this capability, and recommends federal support through R&D grants, procurement incentives, and CAPEX cost-sharing to incubate domestic EBW-NCRF manufacturing — with the existing-company model.

43 PARTICLE ACCELERATORS

The crisis in human capital

This overview discusses the current shortfalls in the U.S. national education system with attention to their effects on the aerospace industry and potential remedies. Student-achievement and literacy rates are examined to compare U.S. students to those of other countries, and the sociological and cultural phenomena are listed which can contribute to deficiencies in learning. Intervention programs for young children and for students in math and science are discussed, and corporate mechanisms are described which support scholarly activities. Also examined are teaching resources provided by government agencies that deal with science and technology. The general conclusion of the paper is that the efforts to date are insufficient because they do not address education levels across the country. It is suggested that corporations and communities rather than federal and state governments address the educational shortfalls.

Kersey, E. D. K.

A New Cure for Medical Errors

In May 2000, senior officials of the U.S. Department of Veterans Affairs (VA) and NASA signed an agreement that would commit the two agencies to create the Patient Safety Reporting System (PSRS) to report: events or situations that could have resulted in accident, injury, or illness, but did not, either by chance or through timely intervention (close-calls); unexpected serious occurrences that involved a patient or employee's death, physical injury, or psychological injury; lessens learned; and safety ideas. The VA provided NASA with funding for the initial development of the new system, which automatically removes all personal names, facility names and locations, and other potentially identifying information before entering reports into its database. Designed to complement the VA's current internal reporting systems, the PSRS is modeled after NASA's Aviation Safety Reporting System, which was established in 1975 under a Memorandum of Agreement between the Federal Aviation Administration and NASA and began operation in 1976.

Source record

Commercially Hosted Government Payloads: Lessons from Recent Programs

In a commercially hosted operational mode, a scientific instrument or operational device is attached to a spacecraft but operates independently from the spacecraft s primary mission. Despite the expected benefits of this arrangement, there are few examples of hosted payload programs actually being executed by government organizations. The lack of hosted payload programs is largely driven by programmatic challenges, both real and perceived, rather than by technical challenges. Partly for these reasons, NASA has not sponsored a hosted payload program, in spite of the benefits and visible community interest in doing so. In the interest of increasing the use of hosted payloads across the space community, this paper seeks to alleviate concerns about hosted payloads by identifying these programmatic challenges and presenting ways in which they can be avoided or mitigated. Despite the challenges, several recent hosted payload programs have been successfully completed or are currently in progress. This paper presents an assessment of these programs, with a focus on acquisition, costs, schedules, risks, and other programmatic aspects. The hosted payloads included in this study are the Federal Aviation Administration's Wide Area Augmentation System (WAAS) payloads, United States Coast Guard's Automatic Identification System (AIS) demonstration payload, Department of Defense's IP Router In Space (IRIS) demonstration payload, the United States Air Force's Commercially Hosted Infrared Payload (CHIRP), and the Australian Defence Force's Ultra High Frequency (UHF) payload. General descriptions of each of these programs are presented along with issues that have been encountered and lessons learned from those experiences. A set of recommended approaches for future hosted payload programs is presented, with a focus on addressing risks or potential problem areas through smart and flexible contracting up front. This set of lessons and recommendations is broadly applicable to future hosted payload programs, whether they are technology demonstrations, communications systems, or operational sensors. Additionally, we present a basic cost model for commercial access to space for hosted payloads as a function of payload mass

Andraschko, Mark A.

Verification and Validation Challenges for Adaptive Flight Control of Complex Autonomous Systems

Autonomy of aerospace systems requires the ability for flight control systems to be able to adapt to complex uncertain dynamic environment. In spite of the five decades of research in adaptive control, the fact still remains that currently no adaptive control system has ever been deployed on any safety-critical or human-rated production systems such as passenger transport aircraft. The problem lies in the difficulty with the certification of adaptive control systems since existing certification methods cannot readily be used for nonlinear adaptive control systems. Research to address the notion of metrics for adaptive control began to appear in the recent years. These metrics, if accepted, could pave a path towards certification that would potentially lead to the adoption of adaptive control as a future control technology for safety-critical and human-rated production systems. Development of certifiable adaptive control systems represents a major challenge to overcome. Adaptive control systems with learning algorithms will never become part of the future unless it can be proven that they are highly safe and reliable. Rigorous methods for adaptive control software verification and validation must therefore be developed to ensure that adaptive control system software failures will not occur, to verify that the adaptive control system functions as required, to eliminate unintended functionality, and to demonstrate that certification requirements imposed by regulatory bodies such as the Federal Aviation Administration (FAA) can be satisfied. This presentation will discuss some of the technical issues with adaptive flight control and related V&V challenges.

Nguyen, Nhan T.

Spatiotemporal Downscaling Model for Solar Irradiance Forecast Using Nearest-Neighbor Random Forest and Gaussian Process

Accurate solar photovoltaic (PV) capacity estimation requires high-resolution, site-specific solar irradiance data to account for localized variability. However, global datasets, such as the National Solar Radiation Database (NSRDB), provide regional averages that fail to capture the fine-scale fluctuations critical for large-scale grid integration. This limitation is particularly relevant in the context of increasing distributed energy resources (DERs) penetration, such as rooftop PV. Additionally, it is critical to the implementation of the U.S. Federal Energy Regulatory Commission (FERC) Order 2222, which facilitates DER participation in U.S. bulk power markets. To address this challenge, this study evaluates Nearest-Neighbor Random Forest (NNRF) and Nearest-Neighbor Gaussian Process (NNGP) models for spatiotemporal downscaling of global solar irradiance data. By leveraging historical irradiance and meteorological data, these models incorporate spatial, temporal, and feature-based correlations to enhance local irradiance predictions. The NNRF model, a machine-learning approach, prioritizes computational efficiency and predictive accuracy, while the NNGP model offers a level of interpretability and prediction uncertainty by numerically quantifying correlations and dependencies in the data. Model validation was conducted using day-ahead predictions. The results showed that the average Goodness of Fit (GoF) of the NNRF model of 90.61% across all eight sites outperformed the GoF of the NNGP of 85.88%. Additionally, the computational speed of NNRF was 2.5 times faster than the NNGP. Finally, the NNGP displayed polynomial scaling while the NNRF scaled linearly with increasing number of nearest neighbors. Additional validation of the model on five sites in Puerto Rico further confirmed the superiority of the NNRF model over the NNGP model. These findings highlight the robustness and computational efficiency of NNRF for large-scale solar irradiance downscaling, making it a strong candidate for improving PV capacity estimation and real-time electricity market integration for DERs.

Asiedu, Shadrack (ORCID:0009000646004826)