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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Density of Next-Generation Caustic-Side Solvent Extraction Solvent

This report recommends the appropriate modifier concentration to employ in the Next Generation Solvent (NGS) to be used in the Salt Waste Processing Facility (SWPF) at the Savannah River Site for removal of cesium from legacy tank waste. The Next Generation Caustic-Side Solvent Extraction (NG-CSSX) process employing the NGS is a marked improvement over the original Caustic-Side Solvent Extraction (CSSX) process, as it provides more effective removal of cesium from highly alkaline radioactive wastes and concentrates this removed cesium into an aqueous solution that is easy to vitrify for final disposal. Considerable effort has been devoted to optimizing the chemistry and process conditions of both systems, and their effectiveness has been demonstrated at the pilot scale at the Modular CSSX Unit (MCU). Due to the success of the demonstration and pilot-scale tests, the Salt Waste Processing Facility (SWPF) has been built to process larger volumes of waste with the CSSX process. To accelerate the waste-processing rate of the SWPF beyond its design throughput, plans call for the replacement of the CSSX process by the NG-CSSX process. To implement the NG-CSSX process in equipment optimized for CSSX, adjusting the density of the NGS to match the CSSX solvent density of 0.851 ± 0.0008 g/mL is considered advisable to obtain comparable hydraulic performance. Toward this objective, the density of the NGS has been measured at different temperatures and modifier concentrations to determine that a concentration of 0.650 M Cs-7SB modifier provides the best match for the desired density.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Neptunium (V) Solubility in the Presence and Absence of WIPP Relevant Ligands

CRA (Compliance Recertification Application)-2024 will update the oxidation state specific model used to calculate actinide solubility in the WIPP (Waste Isolation Pilot Plant). The pentavalent Np(V) ion is the most stable ion in solution within the An(V) series. This valence stability of Np(V) in aqueous solution makes Np a useful representative element for studying the aqueous complex chemistry of all An(V), but in the predicted WIPP scenario, this is the only TRU component that increases in the inventory with time as it is the main daughter product of 241 Am decay (alpha, n) so its relative importance increases throughout the 10,000-year performance period of the WIPP, it is only used to represent itself. This work is focused on confirming organic, borate and carbonate effects on solubility of Np(V) in WIPP simulated brines and 5 M NaCl and reassessing the predicted model speciation to strengthen the overall WIPP An(V) model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Performance Limits for Maritime Wide-Area Search (MWAS) Radar

One of the earliest applications for radar was to search for and find maritime vessels on the open sea. Proper design and operation of an airborne Maritime Wide Area Search (MWAS) radar requires an understanding of system performance characteristics and limitations, and furthermore understanding the trades amongst a large number of interdependent system parameters. This report identifies and explores those characteristics and limits, and how they depend on hardware system parameters and environmental conditions. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall MWAS radar system. While the information herein is not new to the literature, its collection into a single report hopes to offer some value in reducing the 'seek time'. Acknowledgements This report was funded by General Atomics Aeronautical Systems, Inc. (GA-ASI) Mission Systems under Cooperative Research and Development Agreement (CRADA) SC08/01749 between Sandia National Laboratories and GA-ASI. General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of privately-held General Atomics, is a leading manufacturer of Remotely Piloted Aircraft (RPA) systems, radars, and electro-optic and related mission systems, including the Predator/Gray Eagle-series and Lynx Multi-mode Radar. -

42 ENGINEERING↗
DOE OSTI2022

Combined Cycle Integrated Thermal Energy Storage “CiTES” (Final Scientific/Technical Report)

The Phase I of this project confirmed the technical feasibility of a Combined Cycle integrated Thermal Energy Storage “CiTES” system, calculated the key performance parameters like power efficiency and costs, and proved its commercial value with full-year simulations for several US electricity markets with high degree of variable renewable generation and volatile hourly electricity prices. The core element of this project is the Electro Thermal Energy Storage (ETES) technology from Siemens Gamesa Renewable Energy GmbH, using thermally stable and inexpensive volcanic rocks as storage material and air as heat transfer medium. This technology is backed by more than 10 years of experience and a 440MMBTU (130MWh-th) pilot plant in Hamburg, Germany, which is in operation since 2019. The integration of this thermal storage in an existing combined cycle power plant (CCPP) is typical power plant technology without any major technology risks. It allows the storage of inexpensive renewable energy during times of surplus renewable generation and the discharge of this energy in times of high energy demand when the fossil plant is in operation. This supplements the fossil power generation with CO2-emission-free energy. The secondary effect of the CiTES system is that a small part of the stored thermal energy is used to keep the heat recovery steam generator (HRSG) and steam turbine (ST) of the combined cycle power plant in hot and ready-to-start condition. This enables the plant to start rapidly when fossil generation is required to satisfy demand as soon variable generation drops off in the evenings or during cloud cover and calm wind periods. Without pre-warming of the HRSG and ST, the CCPP would need several hours for a cold or warm start, burn a lot of gas and release high NOx emissions during start and wouldn’t be able to use the short times of high energy prices in an efficient or economical manner. The economic parameters of CiTES were determined by a full year “8760” simulation using a data set calculation for each of the hours of the year, and historical electricity and gas prices. For consistency, the simulations were focused on the pre-COVID year 2019. The financially most attractive markets were in the Energy Reliability Council of Texas (ERCOT) region, which allowed substantial value generation with arbitrage (charge with cheap energy during renewable surplus times and discharge when energy is needed and expensive). The improvement of flexibility with the CiTES system by pre-heating and warm-keeping of the CCPP allowed for additional power generation during short time periods when demand is high but renewable generation is down; when the hourly energy prices are highest in these markets. The simulations are based on 2019 data, when ERCOT had 27GW of installed photovoltaic (PV) and wind generation. They showed that the created revenue with the prototypically sized CiTES system of 1,000MMBTU (300MWh-th) falls a little bit short of what is expected from a commercially viable investment. The system has optimization opportunities for cost reduction and increased effectiveness which will be realized during a potential Phase II Pre-FEED study following this project. Furthermore, it is safe to assume that a lot of renewable generation capacity will be added all over the US in the coming years. As an example, ERCOT is predicting to more than double its renewable generation from 27GW in 2019 to a forecasted 63GW in 2023. This will increase the amount of renewable overproduction exponentially. This rapid increase of local overproduction and the need to curtail renewable generation is well documented by the California ISO (www.CAISO.com / managing oversupply). However, the simulations also revealed a weakness in the structure of the electricity markets in the US. More specifically, when electricity prices are very low and approaching negative levels, the owners of Variable Renewable Energy (VRE) will curtail a part of their facility to stabilize the price by reducing supply. This results in a situation in which storage facilities, which are integrated in existing fossil assets and don’t have the behind-the-meter benefit of a VRE, won’t be able to purchase low cost – otherwise curtailed – renewable energy off the grid. A special tariff, which motivates VRE owners to sell otherwise curtailed renewable energy to storage facilities (Hydrogen, thermal, pumped hydro, etc.) can solve this issue. The implementation of such a regulating tariff by Independent System Operators, thus avoiding renewable curtailment, is a pre condition for successful commercialization for renewable energy storage technologies. With this advancement of design and technology and improvements in the market environment, it can be expected that the Combined Cycle integrated Thermal Energy Storage proves itself as an important innovation to keep highly efficient, natural gas-based power generation economically successful and relevant for the power industry in the United States of America.

Wolf, Thorsten↗
DOE OSTI2022

6.26 Low Cost Basalt Fiber for Automotive Applications

Vehicle lightweighting is an essential component to the automotive industry to improve fuel economy of internal combustion engine (ICE) vehicles to meet ever improving emission standards and to improve the range of electric vehicles (EV). Composite materials offer high specific modulus and specific strength, which makes them appealing for these light weighting efforts. Sheet molding compounds (SMC) are particularly interesting from an automotive perspective because of the relatively low cost and high volume of producing SMC parts. Traditionally, composite materials for automotive application are glass fiber reinforced because of the attractive price - performance ratio, but basalt fibers are a cost and recycling competitive reinforcement alternative in this market. The aim of this project was to examine the feasibility of utilizing basalt fiber for automotive applications. More specifically, an effort was made to examine different fiber sizings on basalt fiber combined with vinyl-ester (VE) resin, and their performance as part of an SMC process. In addition to offering vehicle lightweighting with fiber reinforced polymer composites, basalt fiber is a fully recyclable material and thus supports the IACMI technical goal of: Demonstrate that the technology is capable at a sufficient scale for >80% recyclability or reuse of fiber reinforced polymer composites in five years into useful components with projected cost and quality at commercial scale competitive with virgin materials on a pathway to 95% recyclability or reuse starting in ten years. Three different fiber sizings were applied to a continuous roving of basalt fiber and compared to a traditional Electrical/Chemical Resistance (E-CR) glass fiber that is typically used in these types of applications. Fiber tows were examined for Loss on Ignition percentage (LOI%), Tex, and tow strength. Some sizings clearly outperformed others, and the ability to process these fibers on a pilot scale SMC line was demonstrated. A test plan for the manufacturing and mechanical testing of SMC panels was developed. This work continues outside the time frame allocated for this project. When this work is completed, it will be added to this report and posted as Appendix C. Glass fiber reinforced SMC materials have already proven feasible as a light weighting method for traditionally steel parts like the Volkswagen (VW) Atlas lift-gate (Figure 1); this project team is seeking the feasibility of basalt fiber as a drop-in replacement for glass fiber reinforced SMC. Sizing development for basalt fibers has proven that the mechanical properties are better than E-glass and closer to S-glass, which makes it an interesting material for SMC applications. Better mechanical properties translate to less material needed to achieve load case requirement for target applications. The business case has already been demonstrated for 100,000 parts per year of glass fiber reinforced SMC Atlas lift-gates compared to traditional steel manufacturing processes. Reduced overhead and assembly costs are offset by glass fiber SMC higher cost per kg beyond 100,000 parts per year, which is still a relatively low volume for the automotive industry. For basalt fiber reinforced SMC to become feasible for automotive applications, the price-performance ratio has to be precisely determined. Based on the mechanical performance it is possible to establish a range of applications and technical solutions in which the potential of basalt SMC can be utilized, while the price of the material can be used to compile the business case for such applications. Based on these business cases and the sustainability indicators, glass fiber reinforcement (or other) materials can be directly substituted. Volkswagen’s commitment to reducing carbon emissions cannot be understated. Basalt fiber shows promise of reducing the carbon footprint in SMC materials, especially if sizing optimizations can be made with thermoplastic based SMC. To fully realize the value of basalt fiber reinforced materials, a lifecycle cost analysis should be performed on basalt’s production and recycling, and then compared against E-glass. From this assessment, a true judgement can be made on the commercialization potential of this material. Figure 1. Example of Fiber Reinforced Polymer Composite Liftgate As a conclusion, we can state that Mafic basalt fiber is not a direct replacement for E-glass or E-CR glass based on price, but should be considered a technical solution when E-glass does not provide adequate performance in a composite design and S-glass, aramid and carbon fibers are too costly. Mafic basalt fiber can be placed on the high-performance fiber spectrum next to S-glass for performance but at one third the price. It should be considered for more technically challenging structural designs wherein the performance can demonstrate 20-25% performance enhancement over E-glass to elicit more strength or a weight reduction. Both Michelman and Mafic produce thermoplastic sizings which, in combination with Nylon and polypropylene resin and fibers, can further advance high speed composite implementations while maintaining an eco-friendly manufacturing process.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Cloud-based implementation of white-box model predictive control for a GEOTABS office building: A field test demonstration

Model predictive control (MPC) has been proven in simulations and pilot case studies to be a superior control strategy for large buildings. MPC can utilize the weather and occupancy schedule forecasts, together with the system model, to predict the future thermal behavior of the building and minimize the overall energy use and maximize thermal comfort. However, these advantages come with the cost of increased modeling effort, computational demands, communication infrastructure, and commissioning efforts. Thus a typical approach is to, often rapidly, simplify the building modeling and MPC optimization problem while paying a price of not reaching the full performance potential. It has been shown that by employing accurate physics-based models, MPC performance can be notably increased closer to its theoretical performance bound. However, implementation of such high-fidelity MPC in real buildings remains a challenge, resulting in a lack of successful field test studies. This work presents the methodology and field test demonstration of a computationally efficient implementation of the white-box MPC in an office building in Belgium. The detailed model of the building is based on first-principle physical equations. The deployment and supervision of MPC operation in a practical setting are supported by an automated cloud-based communication infrastructure. The motivating factor behind the cloud-based architecture is its compatibility with a commercially appealing control as a service concept. The building is equipped with a ground source heat pump (GSHP) and thermally activated building structures (TABS), where the combination of both is also known as GEOTABS. From a control perspective, GEOTABS buildings are particularly challenging systems due to large scale, complex heating, ventilation and air conditioning (HVAC) system, and slow dynamics with time delays. On the other hand, there is an increased potential for energy savings due to the high thermal mass, which acts as thermal storage. The MPC operation is demonstrated during the challenging transient seasons (switching between heating and cooling), and its performance is compared to a traditional rule-based controller (RBC). We provide a proof of concept of real MPC operation for the most difficult seasons with notable GSHP energy use savings equal to 53.5% and thermal comfort improvement by 36.9%. Other MPC applications found in the literature describe tests for only cooling or only heating, and up to now only for a black-box or a grey-box approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Predicting initial trans-membrane pressure across cycles in the ultrafiltration process using random forest

With growing freshwater scarcity, direct potable reuse (DPR) systems that reclaim wastewater for drinking are becoming increasingly important for sustainable water supply. Reliable operation requires minimizing downtime in ultrafiltration (UF) units, where membrane fouling leads to elevated trans-membrane pressure (TMP). This study develops data-driven regression models based on random forest (RF) and autoregressive (AR) approaches to forecast the initial TMP at the start of each UF filtration cycle in a pilot-scale DPR system. The RF model consistently outperforms baseline methods, including historical mean, last observation carried forward, and AR models, across multiple forecast horizons, achieving the lowest root mean square error. To evaluate how different classes of process variables contribute to TMP dynamics over time, we examine the feature importance of independent input variables across multiple forecast horizons. This analysis provides insight into the temporal relevance of operational and sensor-derived features, guiding control and monitoring strategies. Additionally, the impact of hyperparameter tuning on TMP prediction performance is assessed for both direct and recursive RF modelling approaches. The proposed RF framework establishes a robust foundation for predictive monitoring and real-time optimization of UF operations, supporting sustainable and reliable water reuse.

direct potable reuse↗
DOE OSTI2022

Estimation of process steady state with autoregressive models and Bayesian inference

To improve efficiency, separations engineers will typically design process circuits containing recirculating streams, which mix one or more of the process outputs with the feed material. Doing so can improve efficiency, but will cause a delay in the system reaching steady state conditions until the recirculating load mass flows stabilize. In testing separation circuits, engineers will often test a variety of factors and complete an analysis from sample results. Knowledge of if a process is at steady state, as well as the steady state conditions of a process, is essential for a valid techno-economic analysis. However, the definition of process steady state is often poorly defined, or does not include uncertainty quantification. If the performance of a process operating under two different sets of conditions are compared, an engineer who does not test for steady state or quantify steady state conditions risks producing a faulty analysis. In this work, a Bayesian statistical method for testing if all streams are at steady state is further motivated and then derived. Then after testing for steady state, the same model is used with a prior distribution that enforces a steady state assumption to estimate steady state conditions. Further, these methods were validated in a solvent extraction pilot plant where steady state conditions for all outflows were inferred with uncertainty quantification. Analysis is completed with functions available to the reader as part of the BayesMassBal (V 1.1.0) software package written in R.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Experimental Investigation of Polymer-Induced Fouling of Heater Tubes in the First-Ever Polymer Flood on Alaska North Slope Part II

A polymer flood pilot has been ongoing in the Schrader Bluff viscous oil reservoir at Milne Point on the Alaska North Slope. The results from the pilot are encouraging. However, a major concern of the operator is the influence of polymer on the production system after breakthrough, especially the fouling in heat exchangers. This work applies a multiexperimental approach to study the severity of polymer-induced fouling in both dynamic and static states of produced fluids to determine safe operating conditions. Dynamic scale loop (DSL) tests were conducted to study fouling due to polymer at different skin temperatures (165–350°F) in a dynamic state of fluid flow where the fluids’ flow mimics the residence time of fluids in the heat exchanger of the field pilot. Static deposit tests were also conducted at similar skin temperatures of 165–250°F using a novel experimental apparatus designed and built in-house. It was found that at higher skin temperatures of 250–350°F, tube blocking was observed in the DSL tests, whereas the tests at 165–200°F did not show any tube blocking, even in a more extended test period. The deposit test showed that the deposit rate generally increases with skin temperature, and the presence of polymer aggravates the fouling. The copper tube performs best when the skin temperatures are 165–200°F, while the stainless steel tube performs best at a skin temperature of 250°F. These experiments also manifested the influence of the cloudpoint of the solution as the deposit rate increased significantly when the skin temperature was higher than the solution cloudpoint. The study provides a source of practical guidance to the field operations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

An Applied Strategy for Using Empirical and Hybrid Models in Online Monitoring

The monitoring of plant equipment for failure prediction is one of the key contributors to operation and maintenance (O&M) costs for a nuclear power plant (NPP) because O&M monitoring depends on labor-intensive activities that are required to meet high equipment reliability standards. These activities rely primarily on humans for information gathering, condition diagnosis, and predictive analysis. Online monitoring aims to automate these activities by relying on sensors to replace human information gathering and machine learning to replace human analysis and decision making. To facilitate automated monitoring, a systematic strategy for anomaly detection is needed to optimally use the available sensor data, empirical models, and physics-supported models. This strategy is essential to provide credible reasoning on why and when an empirical (i.e., purely data-driven) versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. The extant methods usually adopt an ad hoc trial-and-error approach that, in addition to being time-consuming and costly, is also highly subjective; it is impacted by the background and the skill set of the personnel making the decisions. Thus, such an approach cannot guarantee an optimum outcome. This represents the motivation of the current research effort, which is focused on devising a scientifically supported strategy for the optimum selection of anomaly detection methods. This report presents a detailed assessment of the main anomaly detection techniques within the empirical or hybrid method streams. Empirical methods include pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The listed techniques within these two streams represent the vast majority of techniques performed for anomaly detection. Using the techniques as outcomes, a strategy was developed to enable a systematic decision-making process to lead to one of these techniques. The strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability and suitability for training and testing, cause-effect, entropy inference, and model fitting. Each of these decision points in the strategy is explained in detail in this report with examples, along with the scientific basis behind the decisions and outcomes in common and simplified terminology. The strategy is developed for use by any NPP staff with basic engineering or science knowledge. A user-friendly graphical state flow diagram was also developed as a visual presentation of the strategy. The strategy was tested and demonstrated through two pilot projects for the application of anomaly detection at an NPP. Each pilot had two use cases: an initial case in which certain decisions were made that resulted in one or more empirical techniques and a revised use case where one or more key decisions were modified resulting in using a set of hybrid methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

A dynamic thermal algal growth model for pilot-scale open-channel raceways

Here this study describes the makeup of and results from a simulation consisting of a lumped thermal model integrated with a dynamic algae growth model to simulate the microalgae productivity of an open-channel raceway cultivation system. The thermal model considers the dynamic effects of weather, light absorption, convective heat transfer, radiation heat transfer, conductive heat transfer, thermal capacitance, and water control strategies. The dynamic algae growth model solves a set of ordinary differential equations consisting of growth functions dependent on incident radiation, temperature, nutrient availability, basal metabolism, and losses due to dark- and photo-respiration. Relative errors in the predicted ash-free dry weight of Nannochloropsis oceanica are 12.5%, -6.1%, and 4.4% for three separate replicates of cultivation cycles (~4.2 m 2 ) performed at AzCATI during the ATP 3 Unified Field Studies in Fall, Spring, and Summer. This research demonstrates that thermal modeling is an essential contributor to the validation of microalgae growth models.

09 BIOMASS FUELS↗
DOE OSTI2022

Resource Recovery and Environmental Protection in Wyoming’s Greater Green River Basin Using Selective Nanostructured Membranes (Final Report)

Produced water (PW) represents a sizable waste stream that is co-generated with oil and natural gas production. In 2021 Wyoming ranked 8th and 9th, respectively in domestic oil and natural gas production. In 2017 Wyoming ranked as the 4th highest generator of PW in the U.S, accounting for 7% of the total volume generated. In the context of being the 3rd most arid state in the U.S., the value of water reuse becomes obvious. PW reuse, and resource recovery, in any form requires some level of treatment to remove particulates, residual (free, dispersed) hydrocarbons, organics, and salts. The level of treatment depends on the requirements of the reuse, or resource recovery, application. PW management systems in Wyoming employ in order of volume of PW managed the following management strategies: reinjection for enhanced oil recovery, surface discharge, deep well injection, evaporation ponds (impoundments), and commercial management/treatment. Complicating treatment efforts are the relatively high concentrations of organics (natural and synthetic), dispersed/free hydrocarbons, benzene-toluene-ethylbenzene, and xylenes (BTEX) compounds, biologicals, salts, and minerals. Hydrocarbons (dispersed/dissolved crude oils) and BTEX compounds, as well as synthetic organics, present economic and environmental concerns. The former represents lost revenue, while the latter results in negative environmental impacts like emissions from surface impoundments. The overall objective of this proposal was to synthesize superhydrophilic/oleophobic and superhydrophobic/oleophilic membranes for selectively concentrating and then separating BTEX compounds and oil and grease (O&G) from PW originating from the Greater Green River Basin (GGRB) in Wyoming. Three specific research aims were pursued to accomplish this overall objective. This final report details the development of the superhydrophobic and superhydrophilic membranes, as well as the design of the membrane module prototypes specifically. The technoeconomic assessment is separately reported in another document. 1. Aim #1 – Material optimization and performance evaluation of superhydrophilic/oleophobic and superhydrophobic/oleophilic membranes made by electrospinning/spraying. 2. Aim #2 – Design and construction of cross-flow membrane modules for selectively concentrating and then separating BTEX/oil from GGRB produced water. 3. Aim #3 – Techno-economic assessment of BTEX/oil recovery, and clean water production, using superhydrophilic/oleophobic and superhydrophobic/oleophilic membrane separation for GGRB PW. Superhydrophobic membranes were synthesized by electrospinning poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) nanofibers onto polyester (PET) substrates and electrospraying nano-carbon black/PVDF-HFP onto the nanofibrous layer. These membranes were characterized by high (>8000 liters per square meter per hour per bar (LMH/bar)) permeance values for pure hydrocarbon phases and a high hydrocarbon selectivity (>96%) when treating GGRB PW. All results were obtained when operating the membrane in a crossflow configuration representative of actual field operating conditions. Solvent/oil properties, specifically viscosity and total surface energy/tension, affected permeance across the membrane, which resulted in light mineral oil (394 LMH/bar) and o-xylene (1834 LMH/bar) being characterized by lower permeance values in the pure phase tests. Mixed phase fluxes between 40 to 80 LMH were obtained for the PW when operating the membrane at a feed pressure of 0.3 bar. Flux decreased as the mixed phase concentration in the feed decreased pointing to the importance of maximizing the collision efficiency between the emulsion and the membrane surface and maximizing the emulsion concentration in the feed and the turbulence within the feed channel. These tests demonstrated that the superhydrophobic membranes developed here are a viable hydrocarbon recovery method for GGRB PWs and should be pursued for testing in pilot-scale trials. Superhydrophilic membranes were successfully synthesized via electrospinning/spraying using polyacrylonitrile (PAN) nanofibers as a base nanofibrous matrix. Integration of polyaniline (PANI) into the nanofibrous matrix produced a superior membrane, for water filtration applications, relative to PAN alone and reduced graphene oxide (RGO) when integrated into the nanofibrous matrix. This conclusion was based on the PANI-PAN resistance to flux loss (fouling) when treating model solvent/oil solutions representative of GGRB PWs and field collected PW from the GGRB. The synthesized PAN membranes outperformed a commercially available PAN membrane designed for oil/water separation. This finding indicates that the surface chemical and physical characteristics of the electrospun membranes presents improved properties for filtration of challenging waters like GGRB PWs. The electrospun membranes therefore show promise overall as a substitute for conventionally polymerized membranes in PW treatment applications. The PANI-PAN membrane specifically presents superior performance characteristics for concentration O&G prior to treatment by the hydrocarbon recovery membrane and producing high-quality filtrate for reuse and/or additional treatment (desalination).

02 PETROLEUM↗
DOE OSTI2022

Integrated Risk-Informed Condition Based Maintenance Capability and Automated Platform: Technical Report 3

This project is a collaborative research effort between PKMJ Technical Services LLC, Idaho National Laboratory, and Public Service Enterprise Group (PSEG) Nuclear, LLC. The collaboration, led by PKMJ Technical Services LLC, is part of the industry Funding Opportunity Announcement (FOA) award under Advanced Nuclear Technology Development FOA #DE-FOA-0001817. The pilot demonstration focuses on the Circulating Water System (CWS), an important non-safety-related system that impacts the power generation capability of the plant site. Achieving riskinformed condition-based Predictive Maintenance (PdM) on the CWS will result in significant economic benefits, and the developed methodologies can also be applied to other plant systems. This approach supports an industry goal of ensuring that nuclear power generation remains a viable, economically competitive option in the energy market. Operation and Maintenance (O&M) costs include labor-intensive Preventive Maintenance (PM) programs that involve manually performed inspection, calibration, testing, and maintenance of plant assets at periodic frequencies as well as time-based replacement of assets, irrespective of condition. This project offers an alternative by focusing on riskinformed condition-based maintenance to reduce O&M costs while still maintaining plant health and safety. This report summarizes the progress made toward achieving a risk-informed condition-based maintenance approach. The research and development (R&D) activities presented in this report are associated with development of a nuclear digital platform application, integration of fault signature models, and automated work management processes. The fault signatures and Machine Learning (ML) models are key components in predictive analytics and are heavily leveraged to improve the insights received by existing plant process data sources. Availability of the analysis results within a centralized digital platform enhances efficiency by enabling automation of activities otherwise performed manually. Personnel are presented with enhanced information that can be used to evaluate plant status and risks. Utilizing the enhancements to data analytics supports automated responses, (i.e. issuance of work orders) to address developing equipment faults and thus preventing forced, unplanned shutdowns of components or systems. The R&D activities described within this report lay the foundation for developing and demonstrating a digital automated platform to centralize the implementation of condition monitoring and response to equipment faults. The digital automated platform is cloud-based and designed to enable improved efficiency of plant processes. The digital platform includes content related to maintenance optimization, fault signature analysis, and plant records, which can all be used to support efficiencies when located within a centralized digital platform. These efficiencies could be further enhanced when deployed through industry-wide deployment of the technology to improve insights and processes based upon economies of scale.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Demonstrating Load-Shaping Capabilities of Cost Minimizing Heat Pump Water Heater Controls with Varying Price Profiles

Increased penetration of photovoltaics and electrification of traditionally gas appliances are exacerbating existing challenges in cost-effectively balancing electricity grid supply and demand. Decarbonization without incurring expensive transmission and distribution system capacity increases requires shifting building loads from peak demand times to peak renewable production times. Grid operators are evaluating new ways of encouraging load shifting, including using time-varying price structures to provide a financial incentive. If devices incorporate price-responsive controls, a price profile could be designed to yield a wide variety of load curves as needed to optimize grid functionality. Heat pump water heaters (HPWHs) are an ideal device for price-responsive controls because the storage tank enables them to optimize the timing of electricity consumption without impacting hot water delivery service. This paper presents work demonstrating how price-responsive controls for HPWHs can provide different load profiles, as needed to stabilize the grid, in response to different price profiles. HPWH manufacturers now include web API and CTA-2045 communication capabilities which enable sending load shaping control signals. Pilot studies and preliminary programs have utilized these capabilities with uniform control strategies to reduce 4-9 PM electricity consumption. However, no studies have developed flexible controls capable of both a) responding to constantly varying price profiles and b) customizing logic to match the needs of each HPWH. Berkeley Lab's CalFlexHub project is pioneering price-driven load flexibility by developing and deploying cost-minimizing controls utilizing setpoint setting signals for fleets of HPWHs in response to varying price profiles. Control development is based on simulations using the Flexible Heat Pump Water Heater Performance Predictor which captures the control decisions of a residential, integrated HPWH manufacturer’s on-board controller. The proposed cost-reducing controls respond to constantly changing price profiles, providing the ability to change the price profile to generate load curves as needed to maintain grid stability. Preliminary simulations studying the load shaping capabilities of price-responsive controls on a fleet of 60 HPWHs have demonstrated an average of a) 135.4% increases in load during low-price periods, b) >36.8% reductions in electricity peak-price period, and c) 6.2% electricity cost savings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Comparative Analysis of Rear Irradiance Modeling Methods for Bifacial PV Systems on Single-Axis Trackers Under Varying Albedo Conditions

This study compares three rear-side irradiance modeling methods for bifacial PV systems on single-axis trackers: (i) the 2D View Factor (VF) model in PVsyst(R), (ii) the open-source PVFactors VF model, and (iii) the Ray Tracing (RT) technique using bifacial_radiance. Simulations were benchmarked against field measurements from a pilot PV plant with rear-side sensors at the torque tube height. Results show that all models underestimated the non-uniformity of rear irradiance along the module length and overestimated the total rear irradiance incident on the module. However, since bifacial gain represents only a fraction of the system's total energy, the resulting energy yield differences among methods remained within +- 2 % of measured values, which is typical for such simulations. While the overall energy impact is limited, this study characterizes the specific limitations of each modeling approach, supporting further improvements in bifacial PV performance assessment methods.

14 SOLAR ENERGY↗
DOE OSTI2024

Overview of results from the 2023 DIII-D negative triangularity campaign

Negative triangularity (NT) is a potentially transformative configuration for tokamak-based fusion energy with its high-performance core, edge localized mode (ELM)-free edge, and low-field-side divertors that could readily scale to an integrated reactor solution. Previous NT work on the TCV and DIII-D tokamaks motivated the installation of graphite-tile armor on the low-field-side lower outer wall of DIII-D. A dedicated multiple-week experimental campaign was conducted to qualify the NT scenario for future reactors. During the DIII-D NT campaign, high confinement ($H_\mathrm{98y,2}\gtrsim$ 1), high current ($q_\mathrm{95} \lt$ 3), and high normalized pressure plasmas ($\beta_\mathrm{N} \gt$ 2.5) were simultaneously attained in strongly NT-shaped discharges with average triangularity $\delta_\mathrm{avg}$ = −0.5 that were stably controlled. Experiments covered a wide range of DIII-D operational space (plasma current, toroidal field, electron density and pressure) and did not trigger an ELM in a single discharge as long as sufficiently strong NT was maintained; in contrast, to other high-performance ELM-suppression scenarios that have narrower operating windows. These strong NT plasmas had a lower outer divertor X-point shape and maintained a non-ELMing edge with an electron temperature pedestal, exceeding that of typical L-mode plasmas. Also, the following was achieved during the campaign: high normalized density ($n_\mathrm{e}$/$n_\mathrm{GW}$ of at least 1.7), particle confinement comparable to energy confinement with $Z_\mathrm{eff}\sim2$ , a detached divertor without impurity seeding, and a mantle radiation scenario using extrinsic impurities. These results are promising for a NT fusion pilot plant but further questions on confinement extrapolation and core-edge integration remain, which motivate future NT studies on DIII-D and beyond.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Supporting Bioproducts Industry Growth with a System Dynamics Decision-Support Tool

A bio-based economy requires chemical products as well as fuels to be produced from biomass. Although a variety of universities, government agencies, start-ups and established firms have engaged in bioproduct development, many projects have failed to reach the point of commercialization and commercialized bioproducts struggle to capture and maintain market share. To date, there has been no general research into the factors that contribute to bioproduct failure or success. This work presents the Bioproduct Transition Dynamics (BTD) system dynamics model, a decision-support tool that simulates the bioproduct development process from pre-piloting research through construction of the first commercial-scale plant, as well as the processes of obtaining funding from investors and government agencies. The core of the BTD is a feedback loop between bioproduct developers and funders, which relates development progress measured with indicators such as net present value to funders’ decisions to continue investing. External factors such as feedstock prices, market size and growth, and the existence of bioproduct consumers also influence a development project’s chances of receiving follow-on funding. Virtually any bioproduct can be represented with the BTD: direct replacements, performance-advantaged products, niche and commodity markets can all be modeled. The goal of the BTD project is to inform decisions made by developers in both established firms and start-ups, investors, government agencies, and other stakeholders interested in growing the nascent U.S. bioproducts industry. This talk will cover the general structure and functionality of the BTD, and present results from an analysis performed with the BTD to demonstrate its use as a decision-support tool and the insights it can provide. The goal of the analysis is to identify the most critical factors that lead to direct replacement and performance-advantaged bioproduct projects emerging successfully from the “Valley of Death”, and to determine if these factors differ between the two bioproduct types.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗