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DOE OSTI2026

Corrosion Testing of Refractory in Contact with Molten Glasses Designed for Waste Vitrification – VSL Touchpoint Matrix Glasses (Revision 1)

It is known that the predictive life of the refractory ceramic liner of nuclear waste glass melters is conservative, as demonstrated by performance of these materials such as in the Defense Waste Processing Facility (DWPF).[1] The motivation for this task is to maximize the useful life of the melters that will be operated at the Waste Treatment and Immobilization Plant (WTP), which will in turn minimize procurement and disposal costs and melter outage times, as well as to identify maximum loadings in the waste glass of those species that corrode melter components. This task was initiated jointly with Pacific Northwest National Laboratory (PNNL) with the objective to develop a methodology and model to enable more accurate prediction of refractory service life under prototypic conditions from laboratory-scale material corrosion tests.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Development of a high fidelity CFD model for solvent evaporation and transport in porous structure during battery electrode drying

An efficient battery manufacturing process is the key to the mass production of Electric Vehicles (EV), in which drying is one of the most energy-intensive steps significantly influencing the battery cell performance. An accurate 3D CFD model for drying is essential for predicting the drying mechanism and optimizing its parameters. By optimizing the drying process, it is possible to reduce energy consumption and cost during battery manufacturing, minimize binder loading and maximize active material loading to achieve superior electrochemical performances and facilitate wider and faster public adoption of EV. This project aims to optimize the drying process during electrode manufacturing by leveraging high-fidelity, porous electrode simulations for solvent evaporation. By optimizing this process, we seek to reduce energy consumption during battery manufacturing, while minimizing binder loading and maximizing active material loading, with the overall goal of enhancing electrical vehicle performance.

Horner, Jeffrey Scott [Sandia National Laboratorie↗

DOE OSTI2021

Co-Design of a Fully Electric Hybrid Hydraulic-Electric Architecture (FE-HHEA) for Off-Road Mobile Machines

Off-road mobile machines, such as excavators and wheel-loaders, are typically actuated by hydraulics using internal combustion engines as their power sources. There is a trend towards fully electrifying these machines and improving their efficiencies due to environmental regulations and concerns. In this paper, a control co-design methodology is used to design a Fully Electrified Hybrid Hydraulic-Electric Architecture (FE-HHEA) for an excavator that drastically reduces energy consumption and minimizes the sizes of costly electric components. By optimizing both control operation and the physical design, the co-design methodology takes into account the interaction between these two aspects. The design methodology also illustrates how the system architecture evolves from the previously developed IC engine powered HHEA with the engine replaced by an electric motor to a seemingly very different architecture with fewer components. The optimized system reduces energy consumption by 71% over the baseline system and uses electrical components that are 1/3 the size of an alternate fully electric architecture.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Inactivation of highly transmissible livestock and avian viruses including influenza A and Newcastle disease virus for molecular diagnostics

There is a critical need for an inactivation method that completely inactivates pathogens at the time of sample collection while maintaining the nucleic acid quality required for diagnostic PCR testing. This inactivation method is required to alleviate concerns about transmission potential, minimize shipping complications and cost, and enable testing in lower containment laboratories, thereby enhancing disease diagnostics through improved turn-around time. This study evaluated a panel of 10 surrogate viruses that represent highly pathogenic animal diseases. These results showed that a commercial PrimeStore® molecular transport media (PSMTM) completely inactivated all viruses tested by >99.99%, as determined by infectivity and serial passage assays. However, the detection of viral nucleic acid by qRT-PCR was comparable in PSMTM and control-treated conditions. These results were consistent when viruses were evaluated in the presence of biological material such as sera and cloacal swabs to mimic diagnostic sample conditions for non-avian and avian viruses, respectively. The results of this study may be utilized by diagnostic testing laboratories for highly pathogenic agents affecting animal and human populations. These results may be used to revise guidance for select agent diagnostic testing and the shipment of infectious substances.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Thermoeconomic Evaluation and Optimization of Using Different Environmentally Friendly Refrigerant Pairs for a Dual-Evaporator Cascade Refrigeration System

Applications of dual-evaporator refrigeration systems have recently gained much attention both in academia and industry due to their multiple benefits. In this study, a comprehensive thermodynamic and economic analysis is conducted to evaluate the potential of using several environmentally friendly refrigerant couples and identifies the most suitable one yielding the best economic results. To achieve this goal, a detailed parametric study is conducted, and an optimization process is performed using a particle swarm optimization (PSO) approach to minimize the unit production cost of cooling (UPCC) of the cascade refrigeration system. The results showed that among all selected 18 refrigerant pairs and for all ranges of examined operating parameters, the R170-R161 pair and R1150-R1234yf pair are identified as the best and worst pairs, respectively, from both thermodynamic and economic viewpoints. The results also confirm that R170-R161 pair has an improvement over R717-R744, used as a typical refrigerant pair of cascade refrigeration cycles. For a base case analysis, the COP of R170-R161 and R1150-R1234yf pairs is determined as 1.727 and 1.552, respectively, while their UPCC is found to be $0.395/ton-hr and $0.419/ton-hr, respectively, showing the influence of proper selection of refrigerant pairs on the cascade cycle’s performance. Overall, this study offers a useful thermodynamic and economic insight regarding the selection of proper refrigerant pairs for a dual-evaporator cascade vapor compression refrigeration system.

42 ENGINEERING↗

DOE OSTI2020

High-Frequency, Multiclass Nonintrusive Load Monitoring for Grid-Interactive Residential Buildings

Smart buildings with net-load metering and control capabilities can provide valuable flexibility to grid operators. This article develops a novel approach for high-frequency, multiclass nonintrusive load monitoring (NILM) that enables effective net-load monitoring capabilities with minimal additional equipment and cost. Relative to existing NILM work, the proposed solution operates at a faster timescale, providing accurate multiclass state predictions for each 60-Hz ac cycle without relying on event-detection techniques. The approach is validated using a test bed with residential appliances and shown to have high accuracy, good generalization properties, and sufficient response time to support building grid-interactive control at fast timescales relevant to the provision of grid frequency support services.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Cooperative Load Scheduling for Multiple Aggregators Using Hierarchical ADMM: Preprint

Demand response (DR) serves an important role in improving the efficiency and stability of power systems. In recent years, with advances in communication and smart device technologies, many aggregators have emerged to facilitate end customer participation in DR programs. These aggregators, equipped with customized optimal control algorithms, are capable of providing various grid services. Among them is load scheduling during DR events, namely following a load signal provided by the utility company while minimizing overall customer discomfort. However, as the number of aggregators keeps increasing, it becomes challenging for utility companies to conduct load scheduling for multiple aggregators and generate reference signals for each of them. This paper proposes an optimization framework using hierarchical alternating direction method of multipliers (H-ADMM) to optimally generate load following signals for multiple aggregators. Under this framework, utility and multiple aggregators work in a cooperative manner, aiming at minimizing an overall system cost from different levels of the power system hierarchy, while protecting user privacy. A case study has been conducted in a system with multiple aggregators, based on control of HVAC loads. Experimental results validate the effectiveness of the proposed algorithm.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Advanced control sequences and FDD technology. Just shiny objects, or ready for scale?

Innovations in commercial building control sequences (ASHRAE guideline 36) and fault detection and diagnostics (FDD) technology have the potential to transform existing building operational efficiency by realizing whole-building level savings on the order of 15% and higher. However, several technical and market barriers related to up-front estimation of achievable savings, verifying implementation, and ensuring persistence are slowing down their adoption as a core offering through diverse owner-funded initiatives and rate-payer funded programs. This paper describes a suite of solutions to overcome these barriers to program delivery of advanced HVAC controls integrated with FDD energy management and information system (EMIS) technology. First, the Guideline 36 conformance test offers an automated method to confirm correct sequence implementation by the manufacturer, before field deployment. A successful test of a controller was conducted using a new manufacturer-independent hardware-in-the-loop testbed demonstrating the viability and scalability of this approach. Second, the Guideline 36 energy savings calculator uses modeling paired with high-level user inputs to estimate building-specific savings potential, target cost effective implementation and minimize uncertainty. Initial results indicate the baseline control sequences significantly impact energy savings, however, as much as 50% savings may be possible for the worst-case baseline scenario. Third, a functional specification provides minimum recommended EMIS-FDD capabilities, and best practices to integrate the technology into organizational practice and ensure that advanced control sequences provide persistent savings.

Pritoni, Marco↗

DOE OSTI2021

Optimal Sizing of an Electric Vehicle Charging Station with Integration of PV and Energy Storage

This paper proposes an optimization model for the optimal configuration of an grid-connected electric vehicle (EV) extreme fast charging station considering integration of photovoltaic (PV) and energy storage. The proposed model minimizes the annualized net cost (i.e., maximizes the annualized net profit) of the extreme fast charging station, including investment and maintenance cost of charging ports, PV and energy storage, net cost of purchasing energy from utility and selling energy to EV customers, degradation cost of energy storage and demand charge. The decision variables are number of charging ports, capacity of invested PV and the power and energy ratings of invested energy storage. The Erlang-loss system is adopted to model the EV mobility. Results of numerical simulations indicate that investment of PV and energy storage could increase the annualized profit of the extreme fast charging station. In addition, the impacts of various parameters on the optimal solution are investigated by sensitivity analysis.

Liu, Guodong↗

DOE OSTI2021

A REDUCED ORDER MODELING APPROACH TO PROBABILISTIC CREEP-DAMAGE PREDICTIONS IN FINITE ELEMENT ANALYSIS

This paper introduces a computationally efficient Reduced Order Modeling (ROM) approach for the probabilistic prediction of creep-damage failure. Component-level probabilistic simulations are needed to assess the reliability and safety of high-temperature components. Full-scale probabilistic creep-damage modeling in finite element (FE) approach is computationally expensive requiring many hundreds of simulations to replicate the uncertainty of component failure. To that end, ROM is proposed to minimize the elevated computational cost while controlling the loss of accuracy. It is proposed that full-scale probabilistic simulations can be completed in 1D at a reduced cost, the extremum conditions extracted, and those conditions applied for lower-cost 2D/3D probabilistic simulations of components that capture the mean and uncertainty of failure. The probabilistic Sine-hyperbolic (Sinh) model is selected which in previous work was calibrated to alloy 304 stainless steel. The Sinh model includes probability density functions (pdfs) for test condition (stress and temperature), initial damage (i.e. microstructure), and material properties uncertainty. The Sinh model is programmed into ANSYS finite element software using the USERCREEP.F material subroutine. First, the Sinh model and FE code are subject to verification and validation to ensure the accuracy of the simulations. Numerous Monte Carlo simulations are executed in a 1D model to generate probabilistic creep deformation, damage, and rupture data. This data is analyzed and the probabilistic parameters corresponding to extreme creep response are extracted. The ROM concept is applied where only the extreme conditions are applied in the 2D probabilistic prediction of a component. The probabilistic predictions between the 1D and 2D geometry is compared to assess ROM for creep. The accuracy of the probabilistic prediction employing the ROM approach will potentially reduce the time and cost of simulating complex engineering systems. Future studies will introduce multi-stage Sinh, stochasticity, and spatial uncertainty for improved prediction.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Mobile Hot Cell Digital Twin using Immersive Virtual Environment

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2023

Mobile Hot Cell Digital Twin: End-of-life Management of Disused High Activity Radioactive Sources – 23598

Sealed radioactive sources are utilized for a wide range of applications across nuclear facilities, universities, hospitals, and industry. When these sources reach the end of serviceable life, they become waste. As waste, this radioactive material then goes through a process of recapture and then transfer to long term storage. With the advancement of technology in conjunction with better accessibility of technology, industries are exploring the use of digital automation to enhance productivity, efficiency, and safety while minimizing operation and maintenance costs, health and environmental risks, and uncertainty in the project life cycles. One area for exploration is the use of a digital twin to help design a robust, versatile, and safe solution for recapturing spent sources. We believe this avenue can also provide further advantages in the operations aspect of end-of-life management of spent radioactive sources by reducing the deployment time, increasing operator safety, and reducing operation & maintenance cost. We present a novel digital twin framework for end-of-life management of disused high activity radioactive sources. We have designed and developed a framework that houses a digital twin for visualizing and monitoring the recapture process to inform the engineering and design of a new Mobile Hot Cell. Furthermore, we demonstrate the feasibility of the proposed framework by providing a prototypical implementation, supporting the Mobile Hot Cell and human-machine interface's virtual replication.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2023

Nuclear-Renewable-Storage Systems: Enhancing Planning and Operations of Integrated Energy Systems

Nuclear-renewable-storage integrated energy systems (IES) are multi-carrier energy systems that include not only electricity but also other forms of demands. Because individual IES components must observe their thermo-physical limits, including ramp rates, start-up, and shut-down time, we formulate operations of the IES as an optimization model by minimizing the total operations costs subject to physical limits of all constituent components. In addition, we develop a data-driven approach to improve the computational performance of the economic dispatch model by using reinforcement learning, where an agent is rewarded by meeting demands and penalized otherwise when shifting to the next state.

25 ENERGY STORAGE↗

DOE OSTI2020

DEM and MELT: A Modular and Compact In-Can Melting Technology Dedicated to D and D and Remediation Waste - 20033

The DEM and MELT In-Can vitrification process is designed to process intermediate and high level waste coming for D and D and remediation operations. It is developed to treat liquid and solid waste, to produce a small amount of secondary waste and to minimize investment and operating costs. This In-Can vitrification process is also developed with a compact and modular design and can be adapted regarding nuclear operators' needs and requirements. Furthermore, this robust and simple process is flexible enough to accommodate most uncertainties on waste composition. The DEM and MELT process is developed through the French consortium coordinated by CEA which gathers Orano, ECM technologies and Andra. In the frame of this project, Orano has designed a compact and modular layout of the process allowing an efficient in situ implementation, close to the waste to be treated. This paper presents the compact and modular design of the DEM and MELT process and the way it can be used for a short duration, as a decommissioning tool aimed to be dismantled just after the treatment operation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

DEM and MELT In-Can Vitrification Process for Fukushima Daiichi Water Treatment Secondary Waste - 20034

Fukushima Daiichi Nuclear Power Station was severely damaged by a tsunami induced by the earthquake on March 11, 2011. A large amount of water treatment secondary waste has been generated from the purification work of contaminated water that consists of the water flowing into the reactor building. The Mid and Long-Term Road map specifies that solid waste at Fukushima Daiichi Nuclear Power Station should be stored safely and reasonably according to its characteristics. In order to meet this goal, a versatile treatment solution is needed, and the In-Can vitrification seems to be a suitable solution. The DEM and MELT In-Can vitrification process is being developed and qualified in France to treat waste arising from decommissioning and dismantling operations. This qualification is carried out through the consortium of the DEM and MELT project coordinated by CEA which gathers Orano, ECM technologies and Andra. The DEM and MELT In-Can vitrification process is a robust, simple and versatile in situ vitrification process. It is designed for high or intermediate level waste and is compact enough to be implemented in an existing facility or close to the waste to be treated. It is developed to treat liquid and solid waste, to produce a small amount of secondary waste and to minimize investment and operating costs. The DEM and MELT In-Can vitrification process is also developed with a modular design in order to be adapted to nuclear operators needs and requirements. The In-Can melting process has already been developed and fully qualified by the CEA for Alpha liquid waste and can be rated TRL 7 for this scope. The In-Can vitrification technology is considered as a qualified solution that could be applied for the treatment of waste resulting from the D and D work in Fukushima Daiichi Nuclear Power Station. The feasibility evaluation of the DEM and MELT In-Can vitrification process for Fukushima Daiichi water treatment secondary waste is a project led by Orano, CEA and ANADEC. This R and D project is performed by the funds from the Ministry of Economy, Trade and Industry as The Subsidy Program 'Project of Decommissioning and Contaminated Water Management'. This paper presents the first results of this feasibility evaluation, from the scenarios and glass formulation definition to the industrial implementation feasibility. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Combining Generative Modeling and Advanced Control for Building Scenario Generation

Buildings make up a large portion of energy consumption in the U.S. today. Understanding their energy consumption patterns can improve their efficiency, but requires detailed models that rely on incomplete or unknown information. Previous work has shown that artificial intelligence (AI) can be used to predict missing information and even suggest upgrades to improve building efficiency. However, building upgrades may require undesirable upfront costs. Oppositely, advanced control could improve building efficiency with negligible upfront cost. To explore the tradeoffs between these two approaches, in this work we propose a workflow to compute optimal temperature setpoint schedules to minimize energy consumption and operational cost. Results show that modifying the temperature setpoints in a building using model predictive control (MPC) can effectively reduce its energy consumption and operational cost. This optimal operation cannot fully meet a desired goal. However, we show that by considering MPC in addition to component upgrades, a desired goal can be met with significantly less upfront costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Reinforcement Learning for Load-balanced Parallel Particle Tracing

We explore an online reinforcement learning (RL) paradigm to dynamically optimize parallel particle tracing performance in distributed-memory systems. Our method combines three novel components: (1) a work donation algorithm, (2) a high-order workload estimation model, and (3) a communication cost model. First, we design an RL-based work donation algorithm. Our algorithm monitors workloads of processes and creates RL agents to donate data blocks and particles from high-workload processes to low-workload processes to minimize program execution time. The agents learn the donation strategy on the fly based on reward and cost functions designed to consider processes' workload changes and data transfer costs of donation actions. Second, we propose a workload estimation model, helping RL agents estimate the workload distribution of processes in future computations. Third, we design a communication cost model that considers both block and particle data exchange costs, helping RL agents make effective decisions with minimized communication costs. We demonstrate that our algorithm adapts to different flow behaviors in large-scale fluid dynamics, ocean, and weather simulation data. Our algorithm improves parallel particle tracing performance in terms of parallel efficiency, load balance, and costs of I/O and communication for evaluations with up to 16,384 processors.

Distributed and parallel particle tracing↗

DOE OSTI2020

Environmental and economic optima of solar home systems design: A combined LCA and LCC approach

Here, we compare the economic and environmental optimal design of Solar Home Systems (SHSs) and explore the role of economic incentives (such as tariffs and technology costs) in approximating the two optima. To achieve that, we present a methodology for the environmental and economic evaluation of grid-connected SHSs: user-scale electric systems involving a photovoltaic (PV) power system and a battery energy storage system. The proposed methodology is based on a mixed integer linear programming (MILP) optimization, life cycle assessment and life cycle costing. This methodological framework is applied to a case study involving a typical SHS installation in Italy. The results of the environmental optimal design brought to the evaluation of a 3.25 kW PV assisted by 8.66 kWh of nickel cobalt manganese batteries, whereas the costs of the SHS are minimized by a small PV system (less than 1 kW). Results underline that the environmental optimal configurations rely on battery technologies, which entails a significant cost compared to the grid connection. In contrast, the economic optimal design solutions is less impactful than the grid mix both from an environmental and economic points of view. Thanks to a reduction of batteries and PV costs, the environmental impact of the economic optimal design is expected to decrease in the future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗