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At least 199 records · Page 11

Adaptive Online Model Update Algorithm for Predictive Control in Networked Systems

In this article, we introduce an adaptive on-line model update algorithm designed for predictive control applications in networked systems, particularly focusing on power distribution systems. Unlike traditional methods that depend on historical data for offline model identification, our approach utilizes real-time data for continuous model updates. This method integrates seamlessly with existing online control and optimization algorithms and provides timely updates in response to real-time changes. This methodology offers significant advantages, including a reduction in the communication network bandwidth requirements by minimizing the data exchanged at each iteration and enabling the model to adapt after disturbances. Furthermore, our algorithm is tailored for non-linear convex models, enhancing its applicability to practical scenarios. The efficacy of the proposed method is validated through a numerical study, demonstrating improved control performance using a synthetic IEEE test case.

data-driven model predictive control↗

Establishing Models for Digital Twin of Hydropower Systems Using Probability Density Function Shaping

This paper introduces a digital twin modeling method for hydropower systems with Kaplan turbines using probability density function (PDF) shaping. We first use multilayer perceptron (MLP) model to build the discretized openloop Kaplan unit, where the MLP is trained by historical data. Then we use a proportional integral double derivative (PIDD) controller and a lead-lag exciter to test the obtained digital twin model in a closed-loop fashion. Simulation results show that the proposed digital twin modeling method can accurately capture the dynamics of the Kaplan hydropower unit. Finally, we show that the obtained digital twin can help to optimize the PIDD parameters. Compared with the original PIDD controller, the optimized one can achieve an over 90% improvement on the mean square tracking error.

Yin, Zhun [New York University]↗

Valuation of Distributed Wind Turbines Providing Multiple Market Services

The role of wind turbines has traditionally been limited to providing energy capacity to the grid, but the availability of smart inverters and recent regulatory changes provide the technical and policy capability for wind turbines to also provide ancillary services. However, in contrast to the technical and policy aspects, the valuation of distributed wind turbines providing such services has not been thoroughly studied. This paper presents an optimal market-participation method for distributed wind turbines and valuates different strategies in California Independent System Operator’s balancing area. The services include energy capacity, regulation up and down, and reserves. An optimization problem is formulated to determine optimal power output for each service and demonstrated using historical data for one complete year. The revenues from multiple services are quantified, and a sensitivity analysis is performed to relate market prices with revenues. It is found that the optimal strategy generates 6% more revenue compared to the revenue from participating in the energy market only. Also, the reduced energy prices in future scenarios increase the relative importance of market participation in ancillary services.

Bhatti, Bilal Ahmad↗

Regional Medium-Term Hourly Electricity Demand Forecasting Based on LSTM

This paper aims to forecast high-resolution (hourly) aggregated load for a certain region in the medium term (a few days to over a year). One region is defined as some places with similar climate characteristics because the climate influences people's daily lifestyles and hence the electric usage. We decom- pose the electric usage records into two parts: base load and seasonal load. Considering both temperature and time factors, different deep learning methods are adopted to characterize them. The first goal of our approach is to predict the peak load which is critical for power system planning. Furthermore, our proposed forecast method can provide the depiction of the hourly load profile to provide customized load curves for high- level real-time applications. The proposed method is tested on real-world historical data collected by CAISO, BPA, and PACW. The experimental results show that trained by three years of data, our method could reduce the prediction error for one-year lead hourly load below 5% MAPE, and predict the occurrence of the peak load for next year in CAISO with an error within three days. Furthermore, as a byproduct, an interesting observation on the impact of COVID-19 on human life was made and discussed based on these case studies.

deep learning↗

Techno-Economic Analysis for the Addition of a Thermal Energy Storage System to a Central Plant

Increasing energy demand and rising peak loads present significant challenges for energy management in commercial and institutional settings. As climate change drives greater cooling needs, central plants must navigate the complex tradeoffs between operational efficiency, cost control, and grid stability. Thermal energy storage (TES) systems offer a viable solution by shifting energy consumption from peak to off-peak periods, thereby reducing peak demand, lowering utility expenses, and improving grid resilience. However, the success of TES implementation hinges on appropriate system sizing, effective control strategies, and alignment with local utility rate structures. This article presents a techno-economic analysis of integrating a chilled water TES system into the central plant at California State University, Dominguez Hills. Drawing on historical load profiles and utility tariffs, we assess three TES sizing approaches and their corresponding control strategies from both energy and economic perspectives. This article utilizes a model-based approach to assess the impact of TES sizing and control strategies on the techno-economic feasibility of integrating TES into an existing central plant. The models employed for this analysis were calibrated using 4 years of historical data. Here, the results demonstrated that utility tariffs and the campus's operational profiles dictate the most feasible sizing and control methods. The findings offer valuable insights for institutions and commercial building managers exploring sustainable energy solutions. By demonstrating how optimized TES strategies can improve operational efficiency while achieving financial savings, this study highlights the potential for TES to align performance with cost effectiveness in real-world applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Selective formation of metastable polymorphs in solid-state synthesis

Metastable polymorphs often result from the interplay between thermodynamics and kinetics. Despite advances in predictive synthesis for solution-based techniques, there remains a lack of methods to design solid-state reactions targeting metastable materials. Here, we introduce a theoretical framework to predict and control polymorph selectivity in solid-state reactions. This framework presents reaction energy as a rarely used handle for polymorph selection, which influences the role of surface energy in promoting the nucleation of metastable phases. Through in situ characterization and density functional theory calculations on two distinct synthesis pathways targeting LiTiOPO 4 , we demonstrate how precursor selection and its effect on reaction energy can effectively be used to control which polymorph is obtained from solid-state synthesis. A general approach is outlined to quantify the conditions under which metastable polymorphs are experimentally accessible. With comparison to historical data, this approach suggests that using appropriate precursors could enable targeted materials synthesis across diverse chemistries through selective polymorph nucleation.

36 MATERIALS SCIENCE↗

Hybrid PDES Simulation of HPC Networks Using Zombie Packets

Although high-fidelity network simulations have proven to be reliable and cost-effective tools to peer into architectural questions for high-performance computing (HPC) networks, they incur a high resource cost. The time spent in simulating a single millisecond of network traffic in the highest detail can take hours, even for static, well-behaved traffic patterns such as uniform random. Surrogate models offer a significant reduction in runtime, yet they cannot serve as complete replacements and should only be used when appropriate. Thus, there is a need for hybrid modeling, where high-fidelity simulation and surrogates run side-by-side. Here, we present a surrogate model for HPC networks in which: packets bypass the network, while the network state is left untouched, i.e., suspended. To bypass the network, we use historical data to estimate the arrival time at which every packet should be scheduled at; to suspend the network, all in-flight packets are scheduled to arrive at their destinations, and are kept in the system to awaken as zombies when switching back to high-fidelity. Speedup for a hybrid model is relative to the proportion of surrogate to high-fidelity. This light-weight surrogate obtained up to 76× speedup. Keeping the zombies in the network showed an increase in the accuracy of the high-fidelity simulation on restart when compared to restarting the network from an empty state.

HPC networks↗

Economic Valuation of Coccidioidomycosis (Valley Fever) Projections in the United States in Response to Climate Change

Coccidioidomycosis, or valley fever, is an infectious fungal disease currently endemic to the southwestern United States. Symptoms of valley fever range in severity from flu-like illness to severe morbidity and mortality. Warming temperatures and changes in precipitation patterns may cause the area of endemicity to expand northward throughout the western United States, putting more people at risk for contracting valley fever. This may increase the health and economic burdens from this disease. We developed an approach to describe the relationship between climate conditions and valley fever incidence using historical data and generated projections of future incidence in response to both climate change and population trends using the Climate Change Impacts and Risk Analysis (CIRA) framework developed by the U.S. Environmental Protection Agency. We also developed a method to estimate economic impacts of valley fever that is based on case counts. For our 2000–15 baseline time period, we estimated annual medical costs, lost income, and economic welfare losses for valley fever in the United States were 400,000 USD per case, and the annual average total cost was 3.9 billion USD per year. For a high greenhouse gas emission scenario and accounting for population growth, we found that total annual costs for valley fever may increase up to 164% by year 2050 and up to 380% by 2090. By the end of the twenty-first century, valley fever may cost 620,000 USD per case and the annual average total cost may reach $18.5 billion per year. This work contributes to the broader effort to monetize climate change–attributable damages in the United States.

54 ENVIRONMENTAL SCIENCES↗

Compressive strength of the plastic-bonded explosive surrogate idoxuridine under quasistatic and dynamic compression

Inert simulant materials, or “mocks”, are often used as surrogates for plastic-bonded explosives (PBX) in non-detonative tests in order to mitigate hazards. Mocks should reproduce as many non-detonative properties of the explosive as possible, including structural behavior in a variety of thermal and mechanical environments. Recently, the molecular crystal idoxuridine (IDOX) has been identified as an ideal mock for the main component in the explosive polymer-matrix composite PBX 9501, and has performed favorably under quasistatic loading conditions. Here, in order to assess robustness over a range of mechanical environments, plastic-bonded IDOX was compression tested from 0.001/s to 2000/s strain rates and compared to PBX 9501 historical data. Plastic-bonded IDOX showed good agreement to PBX 9501 across these strain rates, justifying continued development and production as a mock.

Burch, Alexandra C.↗

Addressing delayed case reporting in infectious disease forecast modeling

Infectious disease forecasting is of great interest to the public health community and policymakers, since forecasts can provide insight into disease dynamics in the near future and inform interventions. Due to delays in case reporting, however, forecasting models may often underestimate the current and future disease burden. In this paper, we propose a general framework for addressing reporting delay in disease forecasting efforts with the goal of improving forecasts. We propose strategies for leveraging either historical data on case reporting or external internet-based data to estimate the amount of reporting error. We then describe several approaches for adapting general forecasting pipelines to account for under- or over-reporting of cases. We apply these methods to address reporting delay in data on dengue fever cases in Puerto Rico from 1990 to 2009 and to reports of influenza-like illness (ILI) in the United States between 2010 and 2019. Through a simulation study, we compare method performance and evaluate robustness to assumption violations. Our results show that forecasting accuracy and prediction coverage almost always increase when correction methods are implemented to address reporting delay. Some of these methods required knowledge about the reporting error or high quality external data, which may not always be available. Provided alternatives include excluding recently-reported data and performing sensitivity analysis. This work provides intuition and guidance for handling delay in disease case reporting and may serve as a useful resource to inform practical infectious disease forecasting efforts.

59 BASIC BIOLOGICAL SCIENCES↗

Rural EVSE Planning and Analysis

The dataset includes detailed anonymized public charging station usage from several rural stations on the ChargePoint and Shell Recharge Solutions (formerly Greenlots) networks situated in and around Athens, Ohio, a rural Appalachian community. Both Level 2 and DC fast charging stations are represented. Historical data in the set date back to 2019; additional data will be uploaded semiannually until the project's completion in 2023. Each charging session recorded includes information on date and time, location, charging station level, session duration, energy delivered, and fuel savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Assessment of Methane Generation from the Thermolysis of Organics in Caustic Waste

Methane generation has been detected during thermolytic Hydrogen Generation Rate (HGR) testing of SRS tank waste and in simulant samples. Simulant testing has shown methane generation in the presence of trimethylsilanol (TMS) and radioactive sample testing has shown methane generation in presence of methylmercury, both of which are found within SRS waste tanks. The 2019 report Evaluation of the Current State of Knowledge for Thermolysis of Organics within SRS Waste Forming Volatile Organic Compounds (VOCs) reviewed historical data and assessed literature pertaining to thermolytic methane generation. That review recommended undertaking thermolysis studies on simulated waste to detect and quantify VOCs. The purpose of this assessment is to review chemistry and current knowledge of organics in SRS waste to recommend which organics in SRS waste tanks, if any, should be tested for thermolytic methane generation. An evaluation of observed methane generation rates has been performed to assess the implication for current CSTF controls. Based on the inputs used in this report, it was concluded that no methane generation data observed to date has challenged the existing 5% organic contribution to the Composite Lower Flammability Limit (CLFL) assumption in the CSTF tank farm at temperatures below 100 °C. Evidence shows that thermolytic pathways to methane generation become significant at temperatures >100 °C in caustic waste. Currently, the influences of thermolytic methane production on the flammability of vessels at >100 °C (e.g., evaporators) is unclear. It is recommended that testing should be undertaken using the HGR experimental approach for methane generation. The initial simulant testing should obtain quantitative methane generation rates at elevated temperatures for methylated siloxanes/silanes and methylmercury with the goal of determining the current mechanism for thermolytic methane generation seen in SRS tank waste. The results of this testing should then be compiled and analyzed to ascertain the risk of challenging the current projected organic contribution of 5% to the CLFL at elevated temperatures. Following this testing, an evaluation of possible flammable gas generation in the 2H and 3H Evaporators should be performed to assess the risk of methane generation at the high temperatures employed by the evaporators.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Sulfur Pellets Responses to a Bare and Steel Reflected Pulse of the Oak Ridge National Laboratory Health Physics Research Reactor

The experiments analyzed in this report were conducted at the Health Physics Research Reactor (HPRR), also known as the $\textit{Fast Burst Reactor}$. The reactor was designed and built at Oak Ridge National Laboratory (ORNL) in 1961. The HPRR was an unmoderated, unshielded fast reactor that used highly enriched uranium and molybdenum alloy as fuel. The reactor was initially sent to the Nevada Test Site in 1962, where it was used to evaluate radiation doses received as a result of the Hiroshima and Nagasaki bombings during World War II. A few years later, the reactor was sent back to ORNL to be part of the Dosimetry Application Research (DOSAR) facility shown in Figure 1, which included a reactor building shown on the left (west) of the picture and a control and laboratory building in the upper right corner (northeast). The critical assembly was used for numerous technical studies, including systems calibration, dosimetry, radiobiology of plants and animals, testing of radiation alarms, as well as teaching and training in radiation dosimetry and nuclear engineering. Between 1963 and 1987, the HPRR was operated for thousands of hours, achieving criticality close to 10,000 times and motivating many publications. The HPRR was decommissioned in 1987. The goal of this effort was to use historical data from operation of the HPRR to create a criticality accident alarm system (CAAS) benchmark to be included in the $\textit{International Handbook of Evaluated Criticality Safety Benchmark Experiments}$ (ICSBEP Handbook). A thorough inspection was performed of all available documentation and information available. The most promising experiments that were selected for evaluation were those described in the 1987 ORNL report entitled $\textit{Health Physics Research Reactor Reference Dosimetry}$, ORNL-6240. The report includes reference dosimetry results of the shielded and unshielded configurations of the HPRR after burst operations. Because of changes to the reactor positioning and storage systems that were made in 1985, the previous dosimetry reports became obsolete, and the newly designed experiments were needed to create the HPRR’s adjusted dosimetry data. The various results reported in ORNL-6240 include reference doses and dose equivalents from different conventions at different distances and elevations as determined using the detected neutron fluence and conversion factors. The HPRR neutron fluence was obtained through different methods, including sulfur pellet analysis and threshold detector unit data. Information about the HPRR spectrum was also obtained through Bonner sphere measurements. This benchmark is focused on a part of the measured sulfur fluences reported in Appendix H of ORNL-6240. Standard commercial sulfur pellets were placed at different distances from the HPRR centerline during burst operation and were activated due to the 32 S(n,p) 32 P reaction. The resulting 32 P activity was then measured and the information about the corresponding sulfur fluence and/or neutron dose could be extracted. Many of those measurements have 7 been performed with the HPRR in its bare configuration or with different shields (combinations of Lucite, concrete, steel). All the necessary, precise information about material and/or dimensions of the different shields was not found, so it was decided to focus only on the unshielded and steel-shielded configurations to minimize the benchmark uncertainty. A total of 31 cases (24 unshielded and 7 shielded cases at different positions) of sulfur fluence were selected before evaluation to develop the benchmark.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Identification of SPR Caverns with Multiple Oil Layers

This analysis shows that when lower density crude oil is injected into the top of an underground salt storage cavern containing more dense crude, separate oil phases can form and coexist indefinitely. This has been observed at the U.S. Strategic Petroleum Reserve in spite of geothermal heating and natural convection, which tend to mix the contents of containers with significant vertical extent subjected to wall and bottom heating. Such persistent layering can create operational challenges for meeting delivery specifications if high-value, low-vapor pressure oil becomes trapped below incoming low-density, high-vapor pressure oil, effectively blocking access to the lower layers until the top layer is removed. Previous conceptual models assumed that the oil injection process mixed incoming oil with resident oil in a storage cavern, forming a single oil phase with relatively homogeneous properties. Here, a review of historical data from the Strategic Petroleum Reserve revealed that several caverns contain multiple oil layers. As a result, oil layering needs to be another variable considered when planning oil movements at SPR in order to optimize low-vapor pressure oil availability to assist in oil delivery blending.

02 PETROLEUM↗

Analysis of Microbial Communities as Indicators of Microbially Induced Corrosion Potential in Stainless Steel Piping

The 200 West Area Pump-and-Treat (200W P&T) facility is part of the final remedy decision for the 200 ZP-1 Operable Unit (OU) and is the interim remedial action for 200-UP-1 OU at the Hanford Site. The facility also treats water from other sources across the site, including 200-DV-1 OU perched water, groundwater from the 200-BP-5 OU, and leachate from the Environmental Restoration Disposal Facility. The facility originally operated a biological treatment process for nitrate that resulted in systemic biofouling and loss of injection well capacity, requiring frequent and costly well rehabilitation. Biofouling has also contributed to corrosion of welds and pitting of stainless-steel piping at the facility. The biological treatment for nitrate was suspended at the end of 2019 calendar year to eliminate negative impacts from biological treatments which improve facility operations and treatment of carbon tetrachloride. Evaluation of the 200W P&T facility’s response to operational improvements, specifically the suspension of the biological treatment, provides information on the potential for continued microbially induced corrosion (MIC). To this end, historical data sets (2015-2017) were compared with molecular biological analyses of 200W P&T water samples from 2018-2020 to quantify trends in total microbial biomass and specific microbial indicator species (iron, sulfate, nitrate, and manganese reducing bacteria) known to cause and enhance metal corrosion. Results showed unequivocal reductions (in excess of 90%) in all microbiological indicators measured following the suspension of the biological treatment. Although abundance measurements for all corrosive MIC populations initially declined after removal of the treatment system, nitrate-reducing bacteria (nirK) and sulfate-reducing bacteria remain highly abundant in the system, an order of magnitude higher than the number of cells present prior to the removal of the biological treatment system [5.14e (1.4) cells/L, vs. 1.14e (0.07) cells/L, reported as average (±SD) for n=3]. In addition, there was an unexpected inflection point in 2019 where all microbial indicators increased unexpectedly in abundance in 2020 by as much as two orders of magnitude compared to 2019 samples. Given the limited number of water samples available for this analysis, the cause of the increase in microbial indicators post-biological treatment has not yet been determined. Systematic sampling of the facility for continued monitoring is recommended so that the responses of MIC populations can be evaluated to ensure that further corrosion is avoided, allowing the 200W P&T facility to operate safely and efficiently at design capacity.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

MindSynchro

This report presents the developments and results of MindSynchro project as part of DOE OE FOA 1861. DOE and Pacific Northwest National Laboratory (PNNL) have made available to FOA awardees datasets containing years of real historical data recorded from various phasor measurement units (PMUs) which are installed in three large US interconnections: Texas (IC A), Western (IC B), and Eastern (IC C). The main goal of the project, which was successfully achieved, was to develop methods for detection and identification of events which are relevant for power grid operation. Tasks performed for achieving the project goals included data exploration and pre-processing, the development and application of physics-based features, data analysis and labeling based on unsupervised learning approaches, training and testing of DSSL models for classification of events which are relevant for power grid operation, and deployment of solutions to cloud environments. The methods developed in the project can potentially provide relevant benefits to power grid asset owners/operators in general in terms of situational awareness. Two main types of outcomes can be provided by these tools: Identification of specific relevant power grid event types: Semi-supervised ML methods developed in the project can adequately employ not only the relatively scarce labeled data but also the large amount of available unlabeled data to train models for detection of specific event types. Such methods enable the application of trained models for the detection of events in a population of PMUs much larger than that associated to the labeled events. Support in data labeling / label validation: Labels are critical for training of models for identification of specific types of events. However, labeling large amounts of data is a manual and tedious process. This means that such process is error prone and is not scalable. Methods developed in the project, based on ensembles of clustering models, have been successfully employed for turning manual labeling into a scalable process. Accurate identification of specific relevant events can provide the operators with immediate situational awareness that could otherwise require hours or days of analysis from domain experts. We envision that such methods could be initially employed in support of post-mortem analysis of events and, as confidence is gained, they could be employed for online/real-time support, providing, among other benefits, insights for avoiding major events which could happen due to a combination of smaller ones. On the longer term, related methods could potentially be employed to improve protection and control.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Draft ASME Boiler and Pressure Vessel Code Cases and Technical Bases for Use of Alloy 617 for Constructions of Nuclear Component Under Section III, Division 5

The American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code currently only allows five materials for use in construction of nuclear components for high temperature service. These are: 2.25Cr-1Mo and V-modified 9Cr-1Mo steels, Types 304 and 316 stainless steels and the high nickel Alloy 800H. Since 2005, the US high temperature gas-cooled reactor program has been characterizing elevated temperature mechanical properties of Alloy 617 as the leading candidate construction material for the intermediate heat exchanger. After analysis of these experimental results, along with historical data and additional results available through the Generation IV International Forum, Very High Temperature Reactor, Materials Program Management Board Materials Handbook, a draft ASME Code Case to allow nuclear construction with Alloy 617 for temperatures up to 1750°F (954°C) has been developed. This report contains the Code Case for Low Temperature Service Construction of Section III, Division 5, Subsection HB, Subpart A, Class A and Subsection HC, Subpart A, Class B components, which has been approved in Section II, Materials, and Section III, Rules for Construction of Nuclear Facility Components. Supporting technical justification for the low temperature Code Case is also included. This Code Case allows use of Alloy 617 up to 800°F (425°C). This report also contains an updated draft of a Section III, Division 5, Subsection HB, Subpart B, Class A Code Case for Alloy 617 to qualify it for use in construction of nuclear components up to 1750°F (954°C) for service life up to 100,000 hours. The draft contained in Appendix 4, subject to editorial revision and approval by the ASME Special Task Group on Alloy 617 Code Qualification, will be submitted for approval by letter ballot by the appropriate ASME Committees. The technical justification supporting the Code Case is presented in Appendix 5 of this report. This background document is part of the information package that will be submitted with the Code Case for ballot.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Techno-Economic Wind Blade Manufacturing Model to Identify Opportunities for Cost Improvements Phase II IACMI Project 4.6/4.8

In IACMI Project 4.6 and IACMI Project 4.8, an Excel-based Techno-Economic Model (TEM) of the manufacturing process for composite wind turbine blades and a DELMIA Factory Flow Simulation of a generic wind blade manufacturing facility was developed. Together, these two tools provide a combined economic modeling capability that accounts for the material, labor, overhead and full-lifecycle operating costs associated with wind blade manufacturing as well as the impact of process flow and factory layout on overall manufacturing efficiency. The tools provide a novel means of detailed comparative analysis of the economic feasibility of proposed technologies and process changes for blade manufacturing. The modeling tools were developed with close support from members of industry and visits to multiple blade manufacturing facilities. With industry oversight, a detailed generalized manufacturing process plan and facility layout were developed with manufacturing parameters, material costs and economic factors based on historical data. Dassault Systèmes and the University of Texas at Dallas (UTD) contributed to the development of the Techno-Economic Model by providing macros to enable the generation of Bill of Material (BOM) data from a 3D blade design in either CATIA or NuMAD format, respectively. The TEM was built with the capability to directly import a Bill of Materials for economic analysis, and with the addition of the macros provided by Dassault and UTD, the TEM can directly import blade designs from both CATIA and NuMAD file formats. The modeling tools developed in Project 4.6 were used to investigate four wind blade manufacturing concepts in detail and select one to explore with laboratory-scale experimentation in Project 4.8. The four manufacturing concepts that were investigated were down-selected by the full project team from a larger list of concepts. The selections were made based on a number of criteria ranking viability and level of interest for each concept. The ‘One-Step Close’ manufacturing concept was ultimately selected for investigation in Project 4.8 and the demonstration was performed at the NREL CoMET facility. The TPI advanced manufacturing facility in Warren, RI contributed the production of several prototype components, the designs for which were developed by Janicki Industries. The demonstration project provided clear indication of the viability of the One-Step Close manufacturing concept for blade manufacturing and good validation of the Techno-Economic Model’s prediction of its economic impact.

17 WIND ENERGY↗