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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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At least 37 records · Page 2

Use of the NetBeans Platform for NASA Robotic Conjunction Assessment Risk Analysis

The latest Java and JavaFX technologies are very attractive software platforms for customers involved in space mission operations such as those of NASA and the US Air Force. For NASA Robotic Conjunction Assessment Risk Analysis (CARA), the NetBeans platform provided an environment in which scalable software solutions could be developed quickly and efficiently. Both Java 8 and the NetBeans platform are in the process of simplifying CARA development in secure environments by providing a significant amount of capability in a single accredited package, where accreditation alone can account for 6-8 months for each library or software application. Capabilities either in use or being investigated by CARA include: 2D and 3D displays with JavaFX, parallelization with the new Streams API, and scalability through the NetBeans plugin architecture.

assessment↗

Improving Performance via Energy Efficiency JUSTIFI: Open-Source Software for Identifying and Quantifying Non-Energy Benefits

Energy efficiency is pivotal to achieving operational excellence, as it enhances value while reducing waste. This presentation explores the integration of non-energy benefits (NEBs) into energy efficiency projects, which can lead to risk reduction, value creation, and cost savings. By quantifying NEBs - such as improved safety, decreased pollution, and increased productivity - companies can strengthen their business cases for energy investments, ultimately improving payback periods and aligning with strategic goals. Designed for a diverse audience, from trained auditors to novices in energy assessments, we have developed open-source software called JUSTIFI, NEB finding methodology, and training materials which build on existing frameworks and leverages resources from the U.S. Department of Energy and Better Plants energy system analysis software suite such as MEASUR. This work aims to maximize ROI through NEB identification, utilizing tools like JUSTIFI and the NEBs Discovery Protocol.

97 MATHEMATICS AND COMPUTING↗

OpenEIS Algorithms

The OpenEIS Algorithm package seeks to provide a low-risk path for building owners, service providers and managers to explore analytical methods for improving building control and operational efficiency. Users of this software can analyze building data, and learn how commercial implementations would provide long-term value. The code also serves as a reference implementation for developers who wish to adapt the algorithms for use in commercial tools or service offerings.

Granderon, Jessica↗

Improvements to the Ionizing Radiation Risk Assessment Program for NASA Astronauts

To perform dosimetry and risk assessment, NASA collects astronaut ionizing radiation exposure data from space flight, medical imaging and therapy, aviation training activities and prior occupational exposure histories. Career risk of exposure induced death (REID) from radiation is limited to 3 percent at a 95 percent confidence level. The Radiation Health Office at Johnson Space Center (JSC) is implementing a program to integrate the gathering, storage, analysis and reporting of astronaut ionizing radiation dose and risk data and records. This work has several motivations, including more efficient analyses and greater flexibility in testing and adopting new methods for evaluating risks. The foundation for these improvements is a set of software tools called the Astronaut Radiation Exposure Analysis System (AREAS). AREAS is a series of MATLAB(Registered TradeMark)-based dose and risk analysis modules that interface with an enterprise level SQL Server database by means of a secure web service. It communicates with other JSC medical and space weather databases to maintain data integrity and consistency across systems. AREAS is part of a larger NASA Space Medicine effort, the Mission Medical Integration Strategy, with the goal of collecting accurate, high-quality and detailed astronaut health data, and then securely, timely and reliably presenting it to medical support personnel. The modular approach to the AREAS design accommodates past, current, and future sources of data from active and passive detectors, space radiation transport algorithms, computational phantoms and cancer risk models. Revisions of the cancer risk model, new radiation detection equipment and improved anthropomorphic computational phantoms can be incorporated. Notable hardware updates include the Radiation Environment Monitor (which uses Medipix technology to report real-time, on-board dosimetry measurements), an updated Tissue-Equivalent Proportional Counter, and the Southwest Research Institute Radiation Assessment Detector. Also, the University of Florida hybrid phantoms, which are flexible in morphometry and positioning, are being explored as alternatives to the current NASA computational phantoms.

Semones, E. J.↗

Vind: A Blockchain-Enabled Supply Chain Provenance Framework for Energy Delivery Systems

Enterprise-level energy delivery systems (EDSs) depend on different software or hardware vendors to achieve operational efficiency. Critical components of these systems are typically manufactured and integrated by overseas suppliers, which expands the attack surface to adversaries with additional opportunities to infiltrate into EDSs. Due to this reason, the risk management of the EDS supply chain is crucial to ensure that we are knowledgeable about the vulnerabilities in software and hardware components that comprise any critical part, quantifiable risk metrics to assess the severity and exploitability of the attack, and provide remediation solutions that can influence a prioritized mitigation plan. There is a need to realize cyber supply chain risk management for industrial control systems’ hardware, software, and computing and networking services associated with bulk electric system (BES) operations. This article proposes a blockchain-based cyber supply chain provenance platform (“Vind”) for EDSs to realize data provenance in a cyber supply chain ecosystem.

Bandara, Eranga↗

Automation of Cassini Support Imaging Uplink Command Development

"Support imaging" is imagery requested by other Cassini science teams to aid in the interpretation of their data. The generation of the spacecraft command sequences for these images is performed by the Cassini Instrument Operations Team. The process initially established for doing this was very labor-intensive, tedious and prone to human error. Team management recognized this process as one that could easily benefit from automation. Team members were tasked to document the existing manual process, develop a plan and strategy to automate the process, implement the plan and strategy, test and validate the new automated process, and deliver the new software tools and documentation to Flight Operations for use during the Cassini extended mission. In addition to the goals of higher efficiency and lower risk in the processing of support imaging requests, an effort was made to maximize adaptability of the process to accommodate uplink procedure changes and the potential addition of new capabilities outside the scope of the initial effort.

Ly-Hollins, Lisa↗

An Approach to Automate tools for the Risk Assessment of Digital Instrumentation and Control Systems

Reliable digital instrumentation and control systems (DI&C) are integral for sustaining the continued operation of nuclear power plants. These systems ensure that nuclear reactors operate safely, efficiently, and within regulatory requirements. Yet, the cost of designing and licensing new nuclear DI&C can be prohibitively expensive. Under the U.S. Department of Energy Light Water Reactor Sustainability Program, Idaho National Laboratory has developed a framework for supporting the risk-informed design of DI&C systems by offering methods to support the identification, quantification, and evaluation of risks for various DI&C design architectures. The framework indicates potential software failure modes and provides pathways for quantifying the potential for these software failures, including common cause failures. Using the framework’s systematic approach, challenges for assessing risks within new and existing nuclear DI&C systems can be reduced. Nevertheless, the current framework can be further improved using the convenience of automation. This paper introduces the development of Software for the Hazard Identification and Evaluation of Digital Systems (SHIELDS). SHIELDS is an engineering software package that enables the identification, elimination, and mitigation of potential risks and reduces the burden of deploying reliable DI&C systems. This work introduces plans and techniques to digitize and improve the manual risk assessment modules of the framework. These improvements will save time and increase the repeatability and usability of the framework, making it more accessible to a wider range of users. Ultimately, this introduces SHIELDS and how its modules support efficient development of safe and reliable DI&C systems.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

NRC technical basis for evaluation of its position on protection against common cause failure in digital systems used in nuclear power plants - 378

Digital technology has advantages over analog systems, including automated monitoring and alerts for standby safety functions, and predictive algorithms to maintain critical safety systems. Additionally, digital technology generally has higher reliability and can be designed to reduce single point vulnerabilities. For these reasons many nuclear plants have applied digital technology to safety and non-safety related applications, including reactor protection system, feedwater and turbine controls, etc. with a corresponding significant improvement in trip reduction. Nonetheless, digital instrumentation and control (I and C) systems also present potential new vulnerabilities that need to be assessed, including potential failures due to increased complexity of digital systems, the introduction of unique failure modes due to software (including software common cause failure (CCF)), and limited operating history of digital systems in nuclear safety related applications compared to analog systems. The fact that software is intangible means that common methods, such as analysis or testing, used for detecting CCF may not be effective when applied to software. Consequently, digital technology is perceived to pose a potential risk from the introduction of undetected systematic faults that could result in CCF. Despite the I and C system upgrades and modifications performed to date, the U.S. Nuclear Regulatory Commission (NRC) and industry stakeholders have identified the need to modernize the regulatory infrastructure to efficiently address risks associated with the use of digital technology for nuclear safety applications and address regulatory uncertainties. The NRC's current position on CCF is guided by the staff requirements memorandum (SRM) on SECY 93-087. The SRM provides specific acceptance criteria for the evaluation of CCF, which the staff implemented in the Branch Technical Position (BTP) 7-19. However, industry stakeholders have proposed using methods to characterize the likelihood of software CCF and eliminate it from further consideration in a defense-in-depth and diversity analysis. The NRC's current position does not consider these alternatives, and thus corresponding acceptance criteria is not currently available. The work discussed in this paper assesses the underlying technical basis associated with CCF, provides technical support for updating the NRC position and considers proposed methods for addressing potential CCF in digital systems while enhancing efficiency, clarity, and confidence. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Moore vs. Murphy: Tradeoffs between complexity and reliability in distributed energy system scheduling using software-as-a-service

Software-based optimization of building control strategies, including scheduling, has the potential to improve the performance of existing complex heating, ventilation, and air conditioning (HVAC), storage, and other systems—especially if temporally variable energy production, such as solar thermal or photovoltaics, is included. If reductions in energy bills can be achieved using optimized control strategies that take advantage of cost-saving opportunities, such as time-of-use pricing, the additional bill savings can cover further efficiency investment costs. As computer processing becomes cheaper over time (Moore's Law), opportunities to perform complex control optimization become more abundant, and these can be performed remotely as software-as-a-service (SaaS). However, by “perfecting” our control strategies, we run an increased risk that when something unexpected happens (Murphy's Law), the consequences of failure are greater. This study used simulation to explore the potential benefits of HVAC schedule optimization, delivery, and implementation using a SaaS paradigm, at various levels of complexity. Implementing optimal schedules in a model of an efficient building's HVAC system, the study predicts energy cost savings of up to 10% compared to the naïve reference control strategy. Optimizing more system control variables increases the potential energy cost savings; however, these savings could be compromised by failures in communication inherent in delivering schedules via SaaS. The additional cost of energy resulting from the risk of increased demand charges generally increased with increased communication failure to a much larger extent than the risk of increased energy use charges. This work suggests that moderate improvements in performance, achieved at low cost by simple means, may be more effective than highly optimized schemes, which are more susceptible to failure due to their dependence on complex interactions between systems.

42 ENGINEERING↗

Micrometeoroid and Orbital Debris (MMOD) Testing, Ballistic Limit Equation Definition and Risk Assessment of the Exploration Extravehicular Mobility Unit (xEMU)

A well-known hazard associated with exposure to the space environment is the risk of failure due to an impact from a micrometeoroid and orbital debris (MMOD) particle. As NASA prepares to return astronauts to the moon with the Artemis program, the next generation of spacesuit is in development to support future extravehicular activities (EVAs.) An MMOD impact to the spacesuit is of great concern as a large leak could prevent an astronaut from safely reaching an airlock in time resulting in a loss of life. The exploration extravehicular mobility unit (xEMU) must meet MMOD requirements for multiple environments including those in low earth orbit (LEO) as well as the meteoroid and secondary lunar regolith ejecta environments found on the lunar surface. The subject of this paper is an internal xEMU configuration design developed by NASA Johnson Space Center (JSC) personnel. This paper will expand on the hypervelocity impact (HVI) testing and ballistic limit equation (BLE) definition work that was partially presented at the 2nd International Orbital De-bris (IOC-II) Conference held in Sugar Land, TX in December 2023. The xEMU shares similarities with the legacy Extravehicular Mobility Unit (EMU) spacesuit that is currently used for ISS EVAs, however differences in the layup (e.g., materials, thicknesses, and layers) of the fabric environmental protection garment (EPG), portable life support system (xPLSS) and helmet required an extensive test program to determine ballistic performance. Over 100 hypervelocity impact (HVI) tests were performed by the NASA/JSC HVIT and White Sands Test Facility (WSTF) teams on the xEMU EPG, xPLSS and helmet to generate ballistic limit equations (BLEs) for MMOD impacts. Additionally, over 50 low speed tests (< 1km/s) were performed by the NASA/JSC HVIT and Southwest Research Institute (SwRI) teams on the xEMU EPG, xPLSS and helmet to generate BLEs for lunar ejecta impacts. Post testing, ballistic limit equations used to define the performance of the various regions on the xEMU spacesuit were developed from a generic set of BLEs. The HVI and low speed testing was performed to establish a physical basis for the equations with the co-efficients and exponents of the generic BLEs adjusted to fit the test data. The xEMU BLEs were added to the NASA/JSC software application used for space-craft MMOD risk assessments (BUMPER-3). A finite element model (FEM) of the xEMU spacesuit, which defines the size and shape of the spacesuit as well as the locations of the various shielding configurations, was created based on a solid model provided by the xEMU program office. Using the FEM file and added xEMU BLEs, BUMPER-3 assessments of the xEMU spacesuit for probability of no penetration (PNP) were performed. For the LEO assessment of a typical ISS EVA, the orbital debris and meteoroids environments were defined using the latest engineering models, ORDEM 3.2 and MEM-3 respectively. The lunar sur-face assessment again used the MEM-3 engineering model to define the meteoroid environ-ment along with the current released lunar surface ejecta model, NASA SP-8013 (developed during the Apollo Program). The Space Team in the Natural Environments Branch at Mar-shall Space Flight Center (MSFC) will soon release the new Lunar Meteoroid Ejecta Engineering Model (LMEEM), at which time the xEMU lunar surface EVA will be reassessed. Assessment of the MMOD risk for an 8-hour, 2-person EVA in both LEO and on the lunar surface showed that the xEMU spacesuit meets the program technical requirement of 1 in 2500 failure odds. Similar to the legacy EMU spacesuit, the majority of the MMOD risk (96% of the LEO EVA risk and 99% of the lunar surface EVA risk) is concentrated in regions of xEMU that are comprised primarily of softgoods (arms, legs, and gloves) rather than the hardgoods (xPLSS, hard upper torso and helmet).

Micrometeoroid↗

Fault Management Architectures and the Challenges of Providing Software Assurance

The satellite systems Fault Management (FM) is focused on safety, the preservation of assets, and maintaining the desired functionality of the system. How FM is implemented varies among missions. Common to most is system complexity due to a need to establish a multi-dimensional structure across hardware, software and operations. This structure is necessary to identify and respond to system faults, mitigate technical risks and ensure operational continuity. These architecture, implementation and software assurance efforts increase with mission complexity. Because FM is a systems engineering discipline with a distributed implementation, providing efficient and effective verification and validation (VV) is challenging. A breakout session at the 2012 NASA Independent Verification Validation (IVV) Annual Workshop titled VV of Fault Management: Challenges and Successes exposed these issues in terms of VV for a representative set of architectures. NASA's IVV is funded by NASA's Software Assurance Research Program (SARP) in partnership with NASA's Jet Propulsion Laboratory (JPL) to extend the work performed at the Workshop session. NASA IVV will extract FM architectures across the IVV portfolio and evaluate the data set for robustness, assess visibility for validation and test, and define software assurance methods that could be applied to the various architectures and designs. This work focuses efforts on FM architectures from critical and complex projects within NASA. The identification of particular FM architectures, visibility, and associated VVIVV techniques provides a data set that can enable higher assurance that a satellite system will adequately detect and respond to adverse conditions. Ultimately, results from this activity will be incorporated into the NASA Fault Management Handbook providing dissemination across NASA, other agencies and the satellite community. This paper discusses the approach taken to perform the evaluations and preliminary findings from the research including identification of FM architectures, visibility observations, and methods utilized for VVIVV.

Fault Management↗

Fault Management Architectures and the Challenges of Providing Software Assurance

Fault Management (FM) is focused on safety, the preservation of assets, and maintaining the desired functionality of the system. How FM is implemented varies among missions. Common to most missions is system complexity due to a need to establish a multi-dimensional structure across hardware, software and spacecraft operations. FM is necessary to identify and respond to system faults, mitigate technical risks and ensure operational continuity. Generally, FM architecture, implementation, and software assurance efforts increase with mission complexity. Because FM is a systems engineering discipline with a distributed implementation, providing efficient and effective verification and validation (V&V) is challenging. A breakout session at the 2012 NASA Independent Verification & Validation (IV&V) Annual Workshop titled "V&V of Fault Management: Challenges and Successes" exposed this issue in terms of V&V for a representative set of architectures. NASA's Software Assurance Research Program (SARP) has provided funds to NASA IV&V to extend the work performed at the Workshop session in partnership with NASA's Jet Propulsion Laboratory (JPL). NASA IV&V will extract FM architectures across the IV&V portfolio and evaluate the data set, assess visibility for validation and test, and define software assurance methods that could be applied to the various architectures and designs. This SARP initiative focuses efforts on FM architectures from critical and complex projects within NASA. The identification of particular FM architectures and associated V&V/IV&V techniques provides a data set that can enable improved assurance that a system will adequately detect and respond to adverse conditions. Ultimately, results from this activity will be incorporated into the NASA Fault Management Handbook providing dissemination across NASA, other agencies and the space community. This paper discusses the approach taken to perform the evaluations and preliminary findings from the research.

Fault Management↗

A High-Performance Computing Predictive GNSS Performance Monitor for Autonomous Air Vehicles in Urban Environments

This report offers analysis and design insights for leveraging High-Performance Computing (HPC) to predict line-of-sight (LOS) Global Navigation Satellite System (GNSS) availability in a city. This work is motivated by the emerging fields of Advanced and Urban Air Mobility (AAM/UAM), where regulatory authorities are seeking city-scale, meter-resolution risk forecasting in order to safely integrate new flight missions with existing urban life and infrastructure. This work addresses the technical challenge of efficiently computing urban GNSS satellite visibility to predict GNSS performance metrics under these requirements. We present a new HPC-optimized shadow casting algorithm variant as a ray-based approach to forecasting satellite visibility. We apply this algorithm variant in a software-defined prognostic service which generates a GNSS navigation risk-correlated map as a path planning-style potential field. We detail dominant computational burdens, viable simplifying assumptions, and different algorithmic implementations, intending to demonstrate a baseline of computation time needed by each stage in such a service. We conclude by analyzing the prototype service’s prediction accuracy compared to receiver data from Corpus Christi, Texas. This informs design trade-offs along the dimensions of hardware, computation time, and tolerable forecasting error (including proportions of false positives and false negatives).

GNSS↗

Agile: From Software to Mission Systems

To maximize efficiency and flexibility in Mission Operations System (MOS) design, we are evolving principles from agile and lean methods for software, to the complete mission system. This allows for reduced operational risk at reduced cost, and achieves a more effective design through early integration of operations into mission system engineering and flight system design. The core principles are assessment of capability through demonstration, risk reduction through targeted experiments, early test and deployment, and maturation of processes and tools through use.

Trimble, Jay↗

Surface Systems and Interface Standardization

Space exploration on planetary surfaces will require the use of various surface systems which will likely need to interface with one another. These systems must communicate and share data, as well as distribute power and transfer fluids for sustainable surface operations. Such systems can range from landers, surface habitats, mobility systems, cargo, and In-Situ Resource Utilizations (ISRUs). Previous and current programs have developed space interoperability standards that help aid in reducing potential risks of interface integration. One example of this is the International Deep Space Interoperability Standards (IDSIS) which focuses on deep space exploration. A goal of the Artemis program is to develop a sustained human presence on the lunar surface that would be a training ground for future Mars exploration. Therefore, it will be beneficial to identify interface standards between the surface assets which will help mitigate risk and reduce complexity in the harsh environments of space exploration. A key contribution to sustainability is commonality between hardware and software interfaces. Generic interfaces for data, power, and fluids will reduce risk, promote interoperability, and define standard interfaces across surface exploration projects and programs. Standardized interfaces would be advantageous for improving efficiency and reducing overall complexity, which are critical considerations for future space exploration. Furthermore, it will provide cost reductions to the Artemis programs over their life cycle (in Operations & Maintenance (O&M) and Logistics). Unique proprietary interfaces if considered or allowed would not only increase complexity but also add cost to the programs. Of course, understanding what will work and not work effectively in these unique environments such as the lunar surface is important. These unique environments require much needed intelligent design, prototyping, comprehensive testing, and field experience, utilizing consensus on common interface solutions.

Jaime Gomez↗

Surface Systems and Interface Standardization

A key contribution to surface systems sustainability on Lunar and planetary surfaces is commonality between hardware and software interfaces. Generic interfaces for data, power, and fluids will reduce risk, promote interoperability, and define standard interfaces across surface exploration projects and programs. Standardized interfaces would be advantageous for improving efficiency and reducing overall complexity, which are critical considerations for future space exploration. Furthermore, it will provide cost reductions to NASA’s Artemis program over its life cycle (in Operations & Maintenance (O&M) and Logistics). Unique proprietary interfaces if considered or allowed would not only increase complexity but also add cost to the programs. Of course, understanding what will work and not work effectively in these unique environments such as the lunar surface is important. These unique environments require much needed intelligent design, prototyping, comprehensive testing, and field experience, utilizing consensus on common interface solutions.

Lunar↗

Survey and evaluate Uncertainty Quantification Methodologies

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that will develop and deploy state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models with uncertainty quantification, optimization, risk analysis and decision making capabilities. The CCSI Toolset will incorporate commercial and open-source software currently in use by industry and will also develop new software tools as necessary to fill technology gaps identified during execution of the project. The CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. The goal of CCSI is to deliver a toolset that can simulate the scale-up of a broad set of new carbon capture technologies from laboratory scale to full commercial scale. To provide a framework around which the toolset can be developed and demonstrated, we will focus on three Industrial Challenge Problems (ICPs) related to carbon capture technologies relevant to U.S. pulverized coal (PC) power plants. Post combustion capture by solid sorbents is the technology focus of the initial ICP (referred to as ICP A). The goal of the uncertainty quantification (UQ) task (Task 6) is to provide a set of capabilities to the user community for the quantification of uncertainties associated with the carbon capture processes. As such, we will develop, as needed and beyond existing capabilities, a suite of robust and efficient computational tools for UQ to be integrated into a CCSI UQ software framework.

01 COAL, LIGNITE, AND PEAT↗

Application of Manufacturing Quality Management Principles to PV System Installations

To help SETO/DOE achieve its goals, the IBTS team proposed a project addressing system reliability by improving installation standards and quality management. The proposed approach was designed to help achieve measurable reductions in installation defect density and improvements in the performance of PV systems by optimizing design and installation of residential and commercial PV systems. This approach addressed the soft costs associated with installations and quality management. The project demonstrated improved system reliability and reduced PV system installation costs. The software developed improved operations, decreased risk, and increased the overall value of PV systems across their lifecycle. The project used several data collection methods, including extensive industry surveys, face-to-face high-level interviews at industry conferences, stakeholder teleconferences, and in-depth interviews conducted by IBTS staff. Results from the research found the industry needs a uniform assessment method for national providers to be more efficient; the software should support both code officials and installers; most industry stakeholders would find value in a centralized software system that allows them to collect, report, and review information on in-process and completed solar installations; and mobile solutions that bridge existing knowledge gaps with inspectors and integrate with existing methodologies (such as permitting software) are of great value. The software solution developed is web-based, allowing for national access, and is built on a Google Firebase platform that can handle significant users and data. It can be used onsite or remotely, allowing for code compliance to continue despite ongoing pandemic related delays or shutdowns for local economies. The information provided by the software tool allows users to uniformly assess a system for compliance and use that aggregated data to identify training topics or create internal process designed to improving issues and reducing occurrence. This solution has multiple benefits in managing quality at time of use and promoting an increase in future safety and quality through education. Perhaps most importantly, this software increases public safety by ensuring compliance of installed systems and allows for local AHJs to remotely engage specialized and qualified solar specific expertise for oversite of the installation in their jurisdictions. Data analysis provides the quality feedback loop identifying the root cause of failure and drives installation practices to improve through training and education, resulting in systems with higher performance, greater reliability, and reduced operations and maintenance costs. With the successful completion of this project, the industry can expect reduced soft costs and increased performance and safety and will ultimately benefit from longer performing systems that cost less to operate.

14 SOLAR ENERGY↗