Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cost reduction potential”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 955 records · Page 53

Sustainable Aviation Fuel (SAF) State-of-Industry Report: State of SAF Production Process

GHG emissions related to commercial air travel were already significant, at 10% of the domestic transportation emissions and 3% of the global greenhouse gas emissions prior to the pandemic, and are expected to double by 2050, even with modest projected growth in air travel. Since Sustainable Aviation Fuel (SAF) is the only way that medium to long haul commercial aviation can be decarbonized, a US government wide "SAF Grand Challenge" was issued to encourage industry to develop capabilities to produce SAF, to reduce cost, improve sustainability, build value chains, and to scale production capabilities (1). The targets are to expand current domestic SAF 2022 production by 200X to 3 billion gallons per year by 2030, and then further by 12X to 35 billion gallons by 2050, while achieving life cycle GHG reduction of 50% relative to fossil Jet A. Following the SAF Grand Challenge, the DOE, USDA, EPA and FAA collaboratively developed a comprehensive strategy, outlined in the "SAF Grand Challenge Roadmap" (2), to inform stakeholders of the actions necessary to achieve the above volumetric targets. The purpose of this study is to provide an assessment of the current state of the SAF production industry and identify challenges and hurdles that industry may face in delivering the 2030 goals. This assessment is for the potential feedstocks and conversion pathways expected to contribute to 2030 goals and will generally follow action areas in the SAF Grand Challenge: feedstocks, conversion technology, supply chain, and policy & valuation.

09 BIOMASS FUELS↗

Economical Ground Data Delivery

Data delivery in the Deep Space Network (DSN) involves transmission of a small amount of constant, high-priority traffic and a large amount of bursty, low-priority data. The bursty traffic may be initially buffered and then metered back slowly as bandwidth becomes available. Today both types of data are transmitted over dedicated leased circuits. The authors investigated the potential of saving money by designing a hybrid communucations architecture that uses leased circuits for high-priority network communications and dial-up circuits for low-priority traffic. The architecture presented here may also be applied to any ground station-to-customer network within the range of a common carrier. The authors compare estimated costs for various scenerios and suggest security safeguards that should be considered.

communications↗

Effect of heterostructure engineering on electronic structure and transport properties of two-dimensional halide perovskites

Organic-inorganic halide perovskite solar cells have attracted much attention due to their low-cost fabrication, flexibility, and high-power conversion efficiency. More recent efforts show that the reduction from three- to two-dimensions (2D) of organic–inorganic halide perovskites promises an exciting opportunity to tune their electronic properties. Here, we explore the effect of reduced dimensionality and heterostructure engineering on the intrinsic material properties, such as energy stability, bandgap and transport properties of 2D hybrid organic–inorganic halide perovskites using first-principles density functional theory. We show that the energy stability of engineered perovskite heterostructures is significantly enhanced. The heterostructures with improved stability also show excellent transport properties similar to their bulk counterparts. Furthermore, these layered chemistries demonstrate the advantage of a broad range of tunable bandgaps and high-absorption coefficient in the visible spectrum. The proposed 2D heterostructured material holds potential for nano-optoelectronic devices as well as for effective photovoltaics.

36 MATERIALS SCIENCE↗

Multitask Machine Learning of Collective Variables for Enhanced Sampling of Rare Events

Computing accurate reaction rates is a central challenge in computational chemistry and biology because of the high cost of free energy estimation with unbiased molecular dynamics. In this work, a data-driven machine learning algorithm is devised to learn collective variables with a multitask neural network, where a common upstream part reduces the high dimensionality of atomic configurations to a low dimensional latent space and separate downstream parts map the latent space to predictions of basin class labels and potential energies. Here, the resulting latent space is shown to be an effective low-dimensional representation, capturing the reaction progress and guiding effective umbrella sampling to obtain accurate free energy landscapes. This approach is successfully applied to model systems including a 5D Müller Brown model, a 5D three-well model, the alanine dipeptide in vacuum, and an Au(110) surface reconstruction unit reaction. It enables automated dimensionality reduction for energy controlled reactions in complex systems, offers a unified and data-efficient framework that can be trained with limited data, and outperforms single-task learning approaches, including autoencoders.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Model-based Design Optimization to Achieve the Performance Goals (16.0 SEER/9.5 HSPF), Developing Heat Pump by Using Low-GWP Refrigerants and 5 mm Diameter Tubes

Usage of low-GWP refrigerants can reduce the Green House Gas (GHG) emission of HVAC systems. Our research in previous milestone report has shown that using heat exchangers with 5 mm diameter tubes instead of 9 mm diameter tubes is a promising solution to meet the performance goals of heat pump using low-GWP refrigerants. In addition, the 5mm tube heat exchangers can lead to lower system refrigerant charge and as a result, reduce environmental impact further. However, shifting to small tube diameters requires in-depth heat exchanger design optimization to adapt to the transition to low-GWP refrigerants. In the 2nd quarter of FY21, we conducted multi-objective optimizations using Particle Swarm Optimization algorithm on a residential 5-ton air source heat pump to investigate the potential system performance improvements and material savings. 4 low-GWP refrigerants, ARM20A, ARM20B, R454A and R454C are investigated in this study. The objectives of the optimization are to minimize the heat pump material cost and to maximize the system performance simultaneously. As a result, the HXs material cost is reduced by up to 77% according to the copper and aluminum material price in current market. Under heating mode operation, the smart 4-way valve guarantees that the optimal low-GWP systems maintain or outperform the heating performance of the R410A baseline system. The model-based design optimization yields 18.3-18.9 SEER and 10.6-11.9 HSPF for optimal systems using different low-GWP refrigerants. The initial performance goals (16.0 SEER/9.5 HSPF) are achieved. Furthermore, up to 50% system refrigerant charge reduction is possible in the optimized low-GWP heat pump system using ARM20B. And 91%-95% predicted life-time direct CO 2 emission reduction is achieved by using the optimal 5mm tube low-GWP heat pumps. The significant material saving, charge reduction and direct CO 2 emission reduction help in reducing the environmental impacts of heat pump systems. The optimal heat exchangers resulting from this research can fit into the original baseline indoor and outdoor fan-coil unit. This can reduce the retrofitting effort by minimizing the change in manufacturing and installation of the heat pumps and guarantee the compatibility with end-users’ house structure. Finally, the new products can be easily accepted by manufacturers and end-users.

42 ENGINEERING↗

Next Generation Integrated PV Products Cost and Workflow Analysis (Final Report)

Residential photovoltaic (PV) costs have fallen consistently for over a decade (Ardani et al. 2018). DOE has subsequently developed a new residential PV cost target for 2030 of $0.05/kilowatt hour (SETO 2023). Ardani et al. (2018) conclude that integrated roofing and PV (RIPV) products may be key to achieving the residential target for both new construction and retrofit residential PV. In RIPV, the PV product is incorporated into or replaces the roofing material. RIPV systems can use conventional crystalline or thin-film technologies, may be aesthetically attractive alternatives to traditional racked and mounted PV systems, and may increase building property values (Cook et al. 2023). These products also have the potential to provide customer acquisition, labor, and equipment cost savings over traditional, racked and mounted residential rooftop PV and several companies have recently introduced integrated roofing and PV (RIPV) products (Cook et al. 2023). In 2022, Tesla was the market leader, representing 94% of RIPV capacity installed in 2022 through its Solar Roof offering, while GAF Energy and its Timberline Solar product was second capturing 3% (Feldman et al. 2023). In this project, NREL analyzed three research questions: (1) How do current RIPV products compare to racked and mounted PV in terms of costs, install times and processes? (2) How are RIPV products installed and are there opportunities for cost savings? (3) What are the key barriers to expanding market opportunities for integrating solar and roofing products? In this project, we explored residential RIPV cost reduction opportunities by analyzing installation processes. Our study documented residential RIPV installations at two reroofing sites (20.52 kilowatts) and the equivalent of nine new construction sites (71.75 kW) in California through a methodology known as time and motion study. We also conducted 15 interviews with subject-matter experts to identify barriers and solutions to maximize these products' market penetration.

14 SOLAR ENERGY↗

Hydrogen Infrastructure Analysis for the Port Applications [Slides]

The International Maritime Organization has committed to 50% reduction in GHG emissions by 2050 worldwide as of 2023. This analysis includes performing an inventory and modeling efforts to understand the energy, equipment and cost requirements to support decarbonization of cargo handling and shore power at U.S. Ports, along with assessment of zero- and near- zero emission fuel supplies at or near U.S. ports focused upon Hydrogen technologies. Initial market assessment for ocean going vessels for harbor support and ocean-going vessels is explored. An energy analysis is performed on the port system using a holistic approach and considering the port as an entire ecosystem that functions as a transportation and energy node. Presently, a comprehensive view is lacking for future analysis efforts, this analysis seeks to address this gap in data by evaluating four representative port types and the potential for utilizing hydrogen for the maritime industry. Every port is different, but broadly they could be bracketed into reference cases with scaling factors for the relative size of the port operations. These reference ports are for future use, potentially as baselines for analysis and development of demonstration programs. An equipment inventory for each reference port type (container, bulk, breakbulk, and inland waterway) is presented. A comparative analysis of fuel cell electric and battery electric equipment is conducted based on the following criteria: technology readiness level, refueling/charging time, operational range, energy consumption, and fuel cost savings compared to baseline internal combustion engine equipment. The tradeoffs and synergies between two alternative powertrains is highlighted. Based on energy and infrastructure analysis, average and high equipment utilization profiles across different port types is identified and quantified baseline fuel and electricity demand for various decarbonization scenarios. Based on the portfolio of equipment converted to fuel cell electric, the estimates of initial capital investment are provided for hydrogen refueling stations across ports. An energy demand model is developed that predicts well the all-electric cargo handling equipment annual energy consumption for ports with annual tonnage under 2 million twenty-foot equivalent units (TEUs). The model is a good rubric to follow for further energy demand models that can create a scalable solution to understand the energy needs of cargo handling equipment, whether they are all-electric, hydrogen fuel cell, or powered by another fuel-type. Zero and near-zero emission fuel supply at ports is evaluated looking into the characteristics of hydrogen, ammonia, and methanol as an alternative fuel, as well as the bunkering status. The readiness of reference ports to produce ammonia or methanol and bunker the fuel is examined based on the framework developed by the Global Maritime Forum and Rocky Mountain Institute.

08 HYDROGEN↗

Composite Cryotank Technologies and Demonstration

NASA is exploring advanced composite materials and processes to reduce the overall cost and weight of liquid hydrogen (LH2) cryotanks while maintaining the reliability of existing metallic designs. The fundamental goal of the composite cryotank project was to provide new and innovative technologies that enable human space exploration to destinations beyond low-Earth orbit such as the Moon, near-Earth asteroids, and Mars. In September 2011, NASA awarded Boeing the contract to design, manufacture, and test two lightweight composite cryogenic propellant tanks. The all-composite tanks shown iare fabricated with an automated fiber placement machine using a prepreg system of IM7 carbon fiber/CYCOM 5320-1 epoxy resin. This is a resin system developed for out-of-autoclave applications. Switching from metallic to composite construction holds the potential to dramatically increase the performance capabilities of future space systems through a dramatic reduction in weight. Composite Cryotank Technologies and Demonstration testing was an agency-wide effort with NASA Marshall Space Flight Center (MSFC) leading project management, manufacturing, and test; Glenn Research Center leading the materials; and Langley Research Center leading the structures effort for this project. Significant contributions from NASA loads/stress personnel contributed to the understanding of thermal/mechanical strain response while undergoing testing at cryogenic temperatures. The project finalized in September 2014.

Vickers, John↗

Advanced modeling and simulation of research reactors using dynamic mode decomposition

Full text of publication follows. Due to the ever-increasing safety requirements, the current trend of nuclear reactor analysis is shifting towards high-fidelity multi-physics models, which have a very high computational cost and modelling complexity. As the cost of even a single model run makes it impossible to analyse the behaviour and performance of these models on large-scale commercial plants, it has become even more significant to provide suitable benchmarks to validate and test them extensively. In this sense, research reactors offer a promising solution for the initial validation of high-fidelity models, as they are significantly smaller than commercial reactors and their characteristics are well known. In particular, the reactors of the TRIGA family have been used to assess and validate models and methods for Generation-IV designs, as they have some similar features (such as the dominance of natural convection as cooling mechanism and the difficulties in performing sub-channel analysis using standard codes). Still, the computational requirements of high-fidelity models make them unsuitable for real-time analysis, even following their assessment on research reactors. In this sense, Model Order Reduction (MOR) techniques give an additional strategy to reduce the computational cost of high-fidelity models (whilst preserving sufficient accuracy). In particular, this work focuses on Dynamic Mode Decomposition (DMD), a non-intrusive MOR technique that aims at representing models with explicit temporal dynamics by extracting the time-varying characteristics and the governing structures based only on a set of available data, thus without needing any underlying knowledge of the governing equations. In addition, DMD also computes a low-dimensional surrogate of the dynamic matrix of the system, making it suited for stability analysis and real-time evaluations. This work focuses on the application and validation of the DMD method on the Computational Fluid-Dynamics (CFD) model TRIGA Mark II reactor, also discussing in detail the potentiality of this algorithm as an advanced modelling tool for nuclear reactor analysis. (author)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Testing the Efficacy of Laser Sterilization as A Spacecraft Bioburden Reduction Alternative

As NASA continues to put forth efforts in seeking out life in the solar system with missions like Europa Clipper, Mars Sample Return, and Dragonfly, reducing the bioburden (number of living microbes) on spacecraft is required by NASA policy for the protection of potentially habitable worlds. In this project, we are testing the efficacy of a novel method for laser sterilization on stress tolerant bacterial spores (Bacillus subtilis) using a high energy femtosecond laser. To test the laser, we inoculate metal coupons with Bacillus subtilis spores. After laser treatment, we do a PVA (polyvinyl acetate) peel to recover the spores then we calculate to find the number of spores that survived the treatment. Our results show that within a certain pulse count range, increasing fluence increases sterilization effectiveness. We have demonstrated the ability to reduce viable microbial counts by at least 10-4. By studying laser sterilization, we could change the way spacecraft are sterilized by making the process more efficient and cost-effective.

Planetary protection↗

Thermobifida fusca Cel6B moves bidirectionally while processively degrading cellulose

Abstract Background Cellulose, an abundant biopolymer, has great potential to be utilized as a renewable fuel feedstock through its enzymatic degradation into soluble sugars followed by sugar fermentation into liquid biofuels. However, crystalline cellulose is highly resistant to hydrolysis, thus industrial-scale production of cellulosic biofuels has been cost-prohibitive to date. Mechanistic studies of enzymes that break down cellulose, called cellulases, are necessary to improve and adapt such biocatalysts for implementation in biofuel production processes. Thermobifida fusca Cel6B ( Tf Cel6B) is a promising candidate for industrial use due to its thermostability and insensitivity to pH changes. However, mechanistic studies probing Tf Cel6B hydrolytic activity have been limited to ensemble-scale measurements. Results We utilized optical tweezers to perform single-molecule, nanometer-scale measurements of enzyme displacement during cellulose hydrolysis by Tf Cel6B. Records featured forward motility on the order of 0.17 nm s −1 interrupted by backward motions and long pauses. Processive run lengths were on the order of 5 nm in both forward and backward directions. Motility records also showed rapid bidirectional displacements greater than 5 nm. Single-enzyme velocity and bulk ensemble activity were assayed on multiple crystalline cellulose allomorphs revealing that the degree of crystallinity and hydrogen bonding have disparate effects on the single-molecule level compared to the bulk scale. Additionally, we isolated and monitored the catalytic domain of Tf Cel6B and observed a reduction in velocity compared to the full-length enzyme that includes the carbohydrate-binding module. Applied force has little impact on enzyme velocity yet it readily facilitates dissociation from cellulose. Preliminary measurements at elevated temperatures indicated enzyme velocity strongly increases with temperature. Conclusions The unexpected motility patterns of Tf Cel6B are likely due to previously unknown mechanisms of processive cellulase motility implicating irregularities in cellulose substrate ultrastructure. While Tf Cel6B is processive, it has low motility at room temperature. Factors that most dramatically impact enzyme velocity are temperature and the presence of its native carbohydrate-binding module and linker. In contrast, substrate ultrastructure and applied force did not greatly impact velocity. These findings motivate further study of Tf Cel6B for its engineering and potential implementation in industrial processes.

Johnson, Madeline M. (ORCID:000000029518293X)↗

Evaluation of the potential for wake steering for U.S. land-based wind power plants

The wind power plant-wide control strategy known as wake steering involves the misalignment of upstream turbines with the wind direction to deflect wakes away from downstream turbines, increasing net wind plant power production. In this paper, we evaluate the potential of wake steering for U.S. land-based wind power plants. First, we outline a method for simulating and optimizing wake steering control for existing wind plants by combining the flow redirection and induction in steady state wake steering engineering model with the U.S. Wind Turbine Database and Wind Integration National Dataset Toolkit wind resource dataset. Next, to better understand the potential benefits of wake steering beyond those for existing wind plants, we evaluate the relative impacts of turbine specific power, turbine spacing, and mean wind speed on energy gain and levelized cost of energy (LCOE) using a model land-based wind power plant. For a subset of 60 existing wind plants, assuming a constant turbulence intensity of 8%, wake steering was found to yield an average annual energy production (AEP) gain of 0.80%, equivalent to recovering 13.85% of baseline wake losses. Further, we present a linear approximation between baseline wake losses and AEP gains that can be used to estimate wake steering gains for other wind power plants. Highlighting additional benefits of wake steering, for the model wind power plant we found that energy gains from wake steering enabled an approximate 30% reduction in turbine spacing while keeping LCOE constant.

17 WIND ENERGY↗

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↗

Ultra-High Bypass Engine Aeroacoustic Study

A system study was carried out to identify potential advanced aircraft engine concepts and cycles which could be capable of achieving a 5 to 10 EPNdB reduction in community noise level relative to current FAR36 Stage 3 limits for a typical large-capacity commercial transport aircraft. The study was directed toward large twin-engine aircraft applications in the 400,000 to 500,000 pound take-off gross weight class. Four single rotation fan engine designs with fan pressure ratios from 1.3 to 1.75, and two counter-rotating fan engine configurations were studied. Several engine configurations were identified which, with further technology development, could achieve the objective of 5 to 10 EPNdB noise reduction. Optimum design fan pressure ratio is concluded to be in the range of 1.4 to 1.55 for best noise reduction with acceptable weight and Direct Operating Cost (DOC) penalties.

Gliebe, Philip R.↗

Facile and Scalable Synthesis of Metal- and Nitrogen-Doped Carbon Nanotubes for Efficient Electrochemical CO 2 Reduction

Metal- and nitrogen-doped carbon (M–N–C) is a promising material to catalyze electrochemical CO 2 reduction reaction (CO 2 RR). However, most M–N–C catalysts in the literature require complicated synthesis procedures and produce small quantities per batch, limiting the commercialization potential. In this work, we developed a simple and scalable synthesis method to convert metal-impurity-containing commercial carbon nanotubes (CNTs) and nitrogen-containing organic precursors into M–N–C via one-step moderate-temperature (650 °C) pyrolysis without any other treatment nor the need to add metal precursors. Batches of catalysts in varied mass up to 10 g (150 mL in volume) per batch were synthesized, and repeatable catalytic performances were demonstrated. To the best of our knowledge, the 10 g batch is one of the largest batches of CO2RR catalysts synthesized in the literature while requiring minimal synthesis steps. The catalyst possessed single-atomic iron–nitrogen (Fe–N) sites, enabling a high performance of >95% CO product selectivity at a high current density of 400 mA/cm 2 and high stability for 45 h at 100 mA/cm 2 in a flow cell testing. The catalyst outperformed a benchmark noble-metal nanoparticle catalyst and achieved longer stability than many other reported M–N–C catalysts in the literature. The scalable and cost-effective synthesis developed in this work paves a pathway toward practical CO 2 RR applications. The direct utilization of metal impurities from raw CNTs for efficient catalyst synthesis with minimal treatment is a green and sustainable engineering approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mixed polyester recycling can enable a circular plastic economy with environmental benefits

The mixed and varied nature of fossil-based and bio-based plastic waste requires complex and costly separations to enable compatibility with recycling technologies. A circular plastic economy based on mixed polyesters through cleaving ester bonds to produce monomers, while re-utilizing bio-based monomers to produce high-quality sustainable plastics, charts an exciting solution. However, the feasibility of such a circular economy solution remains underexplored. Here, in this study, we conducted a techno-economic analysis and life-cycle assessment of three polyester depolymerization recycling processes-methanolysis, glycolysis, and acid hydrolysis-for a mixed feedstock (polyethylene terephthalate [PET], polylactic acid [PLA], and polybutylene adipate terephthalate [PBAT]). Methanolysis outperforms glycolysis and hydrolysis economically and environmentally due to more efficient downstream separations, generating products with a 31% decrease in selling price and 21%-46% reduction in acidification, carcinogenic toxicity, fossil-fuel depletion, global warming potential, particulate formation, and smog formation compared to conventional polyester manufacturing. This study highlights the viability of a circular plastic economy for mixed polyesters via a single chemical recycling process.

09 BIOMASS FUELS↗

Development of Prognostic Models Using Plant Asset Data

The recent growth of machine learning and artificial intelligence technologies provides opportunities for leveraging data-driven algorithms to address the problems of diagnostics and prognostics in the nuclear power industry. The use of machine learning and other statistical methods as prognostic models is of particular interest in the nuclear industry to accurately predict future equipment or plant state given a set of measurements. Such predictive capability will enable predictive assessment of component condition and remaining life and allow for condition-based predictive maintenance. The resulting optimization of maintenance scheduling and reduction in unnecessary maintenance activities will lower overall maintenance costs and improve the economics of nuclear power. This report discusses the various aspects of data processing and model development that are likely to influence the performance of prognostic models. Data from a boiling-water reactor was used to evaluate several prognostic models to identify key considerations for developing such models to predict data-driven plant state and equipment degradation condition. Preliminary results indicate the need for data sets that are relevant to the problem at hand and contain signatures that may be correlated to the prediction problem. Assuming such data exist, development of prognostic models using data-driven methods requires an understanding of the various sources of influence on the prediction accuracy (such as the model architecture, data preprocessing approaches, and potentially external factors influencing the equipment or plant system under assessment). Ongoing research is evaluating these factors in greater detail and examining techniques for calculating prediction uncertainty bounds.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Build-to-Replace: A New Paradigm for Reducing Advanced Reactor O&M Costs

Nuclear energy is a carbon free source of reliable, resilient, and dispatchable energy that has the potential to feature prominently in a future energy mix. To this end, many new reactor designs are being developed to help reduce cost and improve safety. Operating and maintenance (O&M) costs can make up a significant portion of lifecycle costs. Traditional approaches for nuclear plant design O&M is to perform significant inspections and testing of plant equipment to extend the life of equipment as long as possible. This is contrasted with approaches used in other industries where equipment is replaced when it is no longer functional in lieu of spending time and resources on maintenance. This research investigated the “build-to-replace” approach for new nuclear power plants. A methodology was developed to evaluate the effectiveness of the “build-to-replace” approach. Several scenarios were developed and analyzed using the approach. Modest reductions in O&M costs were obtained in some cases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗