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At least 163 records · Page 9

Optimal design of power constrained bipolar membrane electrodialysis over a wide brine range

Bipolar membrane electrodialysis enables the in-situ production of high value products (e.g., acid and base) from clean brine, which is essential for a sustainable future. A technoeconomic assessment (TEA) was conducted on extraction of value from brine using the WaterTAP framework to identify optimal cost across a wide design space. Here, in the power constrained regime, increasing supplied salt concentration does not necessarily result in reduced cost or increased NaOH concentration. A detailed analysis elucidates the critical roles of water dissociation, limiting currents, and sodium diffusion play in shaping the landscape of levelized cost. Among these, water splitting predominantly influences the TEA outcomes across most of the optimal design space. Sensitivity analysis further demonstrates that membrane properties controlling water dissociation significantly impact the unit cost. The results indicate that innovations targeting improvements in water disassociation should be prioritised to effectively reduce the levelized cost of product production.

Bipolar membrane electrodialysis↗

The SDSS-IV MaNGA Sample: Design, Optimization, and Usage Considerations

We describe the sample design for the SDSS-IV MaNGA survey and present the final properties of the main samples along with important considerations for using these samples for science. Our target selection criteria were developed while simultaneously optimizing the size distribution of the MaNGA integral field units (IFUs), the IFU allocation strategy, and the target density to produce a survey defined in terms of maximizing signal-to-noise ratio, spatial resolution, and sample size. Our selection strategy makes use of redshift limits that only depend on i-band absolute magnitude (M {sub i}), or, for a small subset of our sample, M {sub i} and color (NUV − i). Such a strategy ensures that all galaxies span the same range in angular size irrespective of luminosity and are therefore covered evenly by the adopted range of IFU sizes. We define three samples: the Primary and Secondary samples are selected to have a flat number density with respect to M {sub i} and are targeted to have spectroscopic coverage to 1.5 and 2.5 effective radii (R {sub e}), respectively. The Color-Enhanced supplement increases the number of galaxies in the low-density regions of color–magnitude space by extending the redshift limits of the Primary sample in the appropriate color bins. The samples cover the stellar mass range 5×10{sup 8}⩽M{sub ∗}⩽3×10{sup 11} M{sub ⊙} h{sup −2} and are sampled at median physical resolutions of 1.37 and 2.5 kpc for the Primary and Secondary samples, respectively. We provide weights that will statistically correct for our luminosity and color-dependent selection function and IFU allocation strategy, thus correcting the observed sample to a volume-limited sample.

79 ASTRONOMY AND ASTROPHYSICS↗

Analytical Model-Based Design Optimization of a Transverse Flux Machine

This paper proposes an analytical machine design tool using magnetic equivalent circuit (MEC)-based particle swarm optimization (PSO) for a double-sided, flux-concentrating transverse flux machine (TFM). The magnetic equivalent circuit method is applied to analytically establish the relationship between the design objective and the input variables of prospective TFM designs. This is computationally less intensive and more time efficient than finite element solvers. A PSO algorithm is then used to design a machine with the highest torque density within the specified power range along with some geometric design constraints. The stator pole length, magnet length, and rotor thickness are the variables that define the optimization search space. Finite element analysis (FEA) was carried out to verify the performance of the MEC-PSO optimized machine. The proposed analytical design tool helps save computation time by at least 50% when compared to commercial FEA-based optimization programs, with results found to be in agreement with less than 5% error.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Design Optimization of Medium-Frequency Transformer for DAB Converters With DC Bias Capacity

Medium-frequency transformer (MFT) dc bias is critical for the safe operation of dual-active-bridge (DAB) converters. To analyze the dc bias, expressions of dc bias are derived for SiC MOSFET DAB converters. It shows that the dc bias is a current source in steady state; thus, a dc bias current capacity is defined and used as a design constraint in the optimization of MFT. The dc bias current capacity is related to core materials, geometric parameters, and flux density, which is analyzed with analytical expression. Optimization equations with geometric variables are derived, which can be solved theoretically or numerically for both interleaved winding (IW) and separated winding (SW) MFT without and/or with leakage inductance design. Based on the optimization equations, different MFT designs for a 150-kW SiC MOSFET DAB converter are compared on the aspects of core materials, winding structures, and without/with leakage inductance design. The combination of IW structure MFT with auxiliary phase shift inductors is chosen, and the assembled prototype is tested with the 150-kW DAB converter. Here, the designed dc bias capacity, temperature rise, and efficiency are verified.

42 ENGINEERING↗

Design Optimization Study on the Single Tank Packed-bed Thermal Energy Storage System

Idaho National Laboratory (INL) is establishing the Dynamic Energy Transport and Integration Lab (DETAIL) as part of its commitment to research on nuclear-renewable hybrid energy systems and associated advanced reactor technologies. DETAIL is designed to allow several different energy systems to work in unison. Current plans include a PWR simulator, high-temperature steam electrolysis (HSTE) unit, and a renewable energy system (e.g., photovoltaics). DETAIL will provide the real world basis for studies on the systems integration and system configurations to be completed. Encompassed in the DETAIL program is the Thermal Energy Storage (TES) system. The TES system is one of the key components in DETAIL because it allows for the delayed release of energy and can be used to simulate storage capabilities currently being considered by utility providers. Of the various TES concepts, this paper deals with the single-tank packed bed TES system. Particular attention is given to the transient thermal behavior of fluid and solid particles within the packed bed thermocline tank and heat storage efficiency influenced by various design parameters. The effects of tank geometry (height-to-diameter ratio), filler size, filler packing ratio and operating temperature differentials are investigated. Based on the parametric study and cost analysis, the optimal TES tank design for DETAIL is discussed.

25 ENERGY STORAGE↗

Artificial Intelligence for Multiphysics Nuclear Design Optimization with Additive Manufacturing

The geometric flexibility of additively manufactured metals and ceramics generates a very large and open design space that requires advanced modeling and simulation tools for physics simulations and the rigorous definition of design problems. This effort deploys artificial intelligence (AI) and machine learning (ML) algorithms to understand the design space, evaluate potential designs, and more efficiently generate optimized results. The Transformational Challenge Reactor (TCR) program is leveraging advances in several scientific areas—including materials, manufacturing, sensors and control systems, data analytics, and high-fidelity modeling and simulation—to accelerate the design, manufacturing, qualification, and deployment of advanced nuclear energy systems. Through a manufacturing-informed design approach, the TCR program seeks to integrate digital data for rapid nuclear innovation; accelerate the adoption of advances in manufacturing, materials, and computational sciences for nuclear applications; and dramatically reduce deployment costs and timelines for new nuclear reactor technologies. This report documents efforts under the TCR program to leverage advanced modeling and simulation techniques driven by AI/ML algorithms on high-performance computing (HPC) systems to yield more optimized TCR core designs. A multiphysics ML surrogate model was developed to run on the HPC architectures. The surrogate model is trained on high-fidelity simulation data of coupled neutronics and thermofluidics and is used to quickly evaluate thousands of candidate core designs in parallel, which drives the evolution of the cooling channel shapes to minimize temperature peaking and material stress. Outcomes from these activities provide design information and feedback into the core design efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

RF Design Optimization for New Injector Cryounit at CEBAF

A new injector superconducting RF (SRF) cryounit with one new 2-cell, B=0.6 cavity plus one refurbished 7-cell, B=0.97, C100 style cavity has been re-designed and optimized for the engineering compatibility of existing module for CEBAF operation. The optimization of 2-cell cavity shape for longitudinal beam dynamic of acceleration from 200keV to 533keV and the minimization of transverse kick due to the waveguide couplers to less than 1 mrad have been considered. Operating at 1497MHz, two cavities has been designed into a same footprint of CEBAF original quarter cryomodule to deliver an injection beam energy of 5MeV in less than 0.27{degree} rms bunch length and a maximum energy spread of 5keV.

43 PARTICLE ACCELERATORS↗

Optimal Design of Food Packaging Considering Waste Management Technologies to Achieve Circular Economy

Plastic packaging plays a fundamental role in the food industry, avoiding food waste and facilitating food access. The increasing plastic production and the lack of appropriate plastic waste management technologies represent a threat to the environmental and human welfare. Therefore, there is an urgent need to identify sustainable packaging solutions. Circular economy (CE) promotes reducing waste and increasing recycling practices to achieve sustainability. In this work, we propose a CE framework based on multi-objective optimization, considering both economic and environmental impacts, to identify optimal packaging designs and waste management technologies. Using mixed-integer linear programming (MILP), techno-economic analysis (TEA), and life cycle assessment (LCA), this work aims to build the first steps in packaging design, informing about the best packaging alternatives and the optimal technology or technologies to process packaging waste. For the economic analysis, we consider the minimum increase in price (MIP) when adding recycling to the cost of each packaging solution, while for the environmental analysis, the greenhouse gas emissions impact was considered. A case study on ground coffee packaging is used to illustrate the proposed framework. The results demonstrate that the multilayer bag option is the most convenient when considering both the chosen economic and environmental impacts.

Life Cycle Analysis↗

An Open-Source Frequency-Domain Model for Floating Wind Turbine Design Optimization

A new frequency-domain dynamics model has been developed that uses open-source components to efficiently represent a complete floating wind turbine system. The model, called RAFT (Response Amplitudes of Floating Turbines), incorporates quasi-static mooring reactions, strip-theory and potential-flow hydrodynamics, blade-element-momentum aerodynamics, and linear turbine control. The formulation is compatible with a wide variety of support structure configurations and no manual or time-domain preprocessing steps are required, making RAFT very practical in design and optimization workflows. The model is applied to three reference floating wind turbine designs and its predictions are compared with results from time-domain OpenFAST simulations. There is good agreement in mean offsets as well the statistics and spectra of the dynamic response, verifying RAFT’s general suitability for floating wind analysis. Follow-on work will include verification of potential-flow and turbine-control features and application to optimization problems.

17 WIND ENERGY↗

Maximized Information Gain of Next Generation Pulsed Power Using Optimized Design of Z-Machine Experiments

This project develops a Bayesian optimization approach to extracting insights from Z Machine experimental data to determine if and how these insights can be used to extrapolate to a larger facility. The primary goal is to address the scientific challenge of informing how confidently experimental conditions can be predicted on a next generation facility, the design of which requires the reliable extrapolation of current high energy density technologies to regimes yet unobserved, except by costly high-fidelity computational models. Maximizing the use of presently available data and understanding how it informs future endeavors is critically important to enable transformative pulsed power and the science of extreme conditions. We explore a Bayesian optimization approach to experimental design which combines information theory, experimental data, and computational modeling to explore how information gain can be maximized.

97 MATHEMATICS AND COMPUTING↗

Optimal Design and Techno-Economic Analysis of 3D-Printed, Intensified Packings for Absorbers and Strippers in Solvent-Based CO 2 Capture

A potential technology for the CO 2 absorption process is utilizing intensified structured packing with embedded cooling/heating channels for continuous heat exchange, which can overcome limitations of discrete methods, such as discrete intercooling and centralized reboilers, to aid in reducing energy consumption and decreasing costs. This work investigates the modeling of intensified packing (IP) for the stripper tower, extending on previous work for the absorber, which distributes heat internally within the column, improving the thermodynamics for the solvent regeneration process. The model includes submodels for steam turbine extraction to produce steam at various qualities as well as a surrogate model for calculating steam enthalpy. A cost model for a plant-scale absorption capture process was developed, allowing for the design of the plant to be optimized, subject to minimizing capture cost using two different power plant flue gas sources. In this optimization, the placement of IP in both towers is optimized to balance the trade-off between enhanced heat transfer and reduced mass transfer volume. For natural gas combined cycle flue gas, the standard process configuration had a minimum cost of $\$$65.40/tonne CO 2 , and considering IP, the minimum capture cost is reduced to $\$$62.73/tonne, with utilization in the stripper column, which reduces yearly costs by up to $\$$2.67 MM/yr. Cooling the absorber through IP, or intercoolers, was only found to be beneficial at higher capture rates, with IP in both towers having a cost of capture of $\$$68.08/tonne at 99.9% capture, a reduction of $\$$12.64/tonne when using only intercoolers at the same capture rate. When capturing from pulverized-coal power plants, the minimum cost of capture when using IP in both towers is $\$$44.18/tonne (at 97% capture), while the standard configuration with and without intercoolers was $\$$45.69 and $\$$47.22 per tonne, respectively. This results in a reduction in yearly costs of $\$$16.98 MM/yr from the base-case configuration. At this higher CO 2 concentration, cooling in the absorber from the IP becomes extremely beneficial, reducing energy consumption by up to 6%.

20 FOSSIL-FUELED POWER PLANTS↗

New Perspectives in Thermoelectric Energy Recovery System Design Optimization

Abstract: Large amounts of waste heat are generated worldwide in industrial processes, automotive transportation, diesel engine exhaust, military generators, and incinerators because 60-70% of the fuel energy is typically lost in these processes. There is a strong need to develop technologies that recover this waste heat to increase fuel efficiency and minimize fuel requirements in these industrial processes, automotive and heavy vehicle engines, diesel generators, and incinerators. There are additional requirements to reduce CO2 production and environmental footprints in many of these applications. Recent work with the Strategic Environmental Research and Development Program office has investigated new thermoelectric (TE) materials and systems that can operate at higher performance levels and show a viable pathway to lightweight, small form-factor, advanced thermoelectric generator (TEG) systems to recover waste heat in many of these applications. New TE materials include nano-composite materials such as lead-antimony-silver-telluride (LAST) and lead-antimony-silver-tin-telluride (LASTT) compounds. These new materials have created opportunities for high-performance, segmented-element TE devices. New higher-performance TE devices segmenting LAST/LASTT materials with bismuth telluride have been designed and fabricated. Sectioned TEG systems using these new TE devices and materials have been designed. Integrated heat exchanger/TE device system analyses of sectioned TE system designs have been performed creating unique efficiency-power maps that provide better understandings and comparisons of design tradeoffs and nominal and off-nominal system performance conditions. New design perspectives in optimization of sectioned TE design approaches are discussed that provide insight on how to optimize such sectioned TE systems. System performance analyses using ANSYS® TE modeling capabilities have integrated heat exchanger performance models with ANSYS® TE models to extend its analysis capabilities beyond simple constant hot-side and cold-side temperature conditions . Analysis results portray external resistance effects, matched load conditions, maximum power vs. maximum efficiency points simultaneously.

Energy Conversion↗

Design optimization of MR-compatible rotating anode x-ray tubes for stable operation

Purpose: Hybrid x-ray/MR systems can enhance the diagnosis and treatment of endovascular, cardiac, and neurologic disorders by using the complementary advantages of both modalities for image guidance during interventional procedures. Conventional rotating anode x-ray tubes fail near an MR imaging system, since MR fringe fields create eddy currents in the metal rotor which cause a reduction in the rotation speed of the x-ray tube motor. A new x-ray tube motor prototype has been designed and built to be operated close to a magnet. To ensure the stability and safety of the motor operation, dynamic characteristics must be analyzed to identify possible modes of mechanical failure. In this study a 3D finite element method (FEM) model was developed in order to explore possible modifications, and to optimize the motor design. The FEM provides a valuable tool that permits testing and evaluation using numerical simulation instead of building multiple prototypes.Methods: Two experimental approaches were used to measure resonance characteristics: the first obtained the angular speed curves of the x-ray tube motor employing an angle encoder; the second measured the power spectrum using a spectrum analyzer, in which the large amplitude of peaks indicates large vibrations. An estimate of the bearing stiffness is required to generate an accurate FEM model of motor operation. This stiffness depends on both the bearing geometry and adjacent structures (e.g., the number of balls, clearances, preload, etc.) in an assembly, and is therefore unknown. This parameter was set by matching the FEM results to measurements carried out with the anode attached to the motor, and verified by comparing FEM predictions and measurements with the anode removed. The validated FEM model was then used to sweep through design parameters [bearing stiffness (1×10{sup 5}–5×10{sup 7} N/m), shaft diameter (0.372–0.625 in.), rotor diameter (2.4–2.9 in.), and total length of motor (5.66–7.36 in.)] to increase the fundamental frequency past the operating range at 50 Hz.Results: The first large vibration during the prototype motor operation was obtained at 21.64±0.68 Hz in the power spectrum. An abrupt decrease in acceleration occurred at 21.5 Hz due to struggling against the resonance vibrations. A bearing stiffness of 1.2×10{sup 5} N/m in the FEM simulation was used to obtain a critical speed of 21.4 Hz providing 1.1% error. This bearing stiffness value and the 3D model were then confirmed by the experiments with the anode removed, demonstrating an agreement within 6.4% between simulation results and measurements. A calculated first critical frequency (fundamental frequency) of 68.5 Hz was obtained by increasing the bearing stiffness to 1×10{sup 7} N/m and increasing the shaft diameter by 68.0%. Reducing the number of bearings in the design permits decreasing the total length of the motor by 1.7 in., and results in a fundamental frequency of 68.3 Hz in concert with additional changes (shaft diameter of 0.625 in., rotor diameter of 2.4 in., and bearing stiffness of 1×10{sup 6} N/m).Conclusions: An FEM model of the x-ray tube motor has been implemented and experimentally validated. A fundamental frequency above the operational rotation speed can be achieved through modification of multiple design parameters, which allows the motor to operate stably and safely in the MR environment during the repeated acceleration/deceleration cycles required for an interventional procedure. The validated 3D FEM model can now be used to investigate trade-offs between generated torque, maximum speed, and motor inertia to further optimize motor design.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Optimized design of reactor cores for continuous operation of Belgian nuclear power plants

Two Belgian nuclear power plants, owned and operated by Electrabel, were initially planned to be phased out in 2015, reaching their maximum life time of operation by the initial design. The fuel management of those two units has been subsequently designed by Tractebel to make the best use of the energy in the fuel assemblies either in the core or in the storage pool and to minimize the size of the fresh reloads in the terminating cycles. However, for ensuring energy security in Belgium, the Government decided in the same year to extend the life time of operation of the two units for 10 years, which raised the need to resume their continuous operation, in the opposite direction of the core contents and with a significant break in the usual sequence of cycle reloads. All this required adaptation of the tools and process for optimized reactor core design, in order to ensure the continuous and flexible operation of those units. The Tractebel LWRWIMS-PANTHER (LWP) core physics package is based on the 3-dimensional (3D) neutronic code PANTHER and the lattice code LWRWIMS for the generation of the assembly nuclear data. Both have been qualified by Tractebel for the Belgian Units to perform a complete range of PWR reactor calculations for fuel management design safety parameters assessment, transient analysis and operational support. In-core fuel management involves calculating core reactivity, power distribution and isotopic inventory for subsequent fuel cycles of a nuclear power plant in order to maintain adequate safety margins and operating lifetime for each core loading. This paper presents Tractebel's improved core design tools and process, the approach to optimize the reactor core design, and the applications to the 2 successive but opposite design requirements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Technoeconomic Design Optimization for Fast Reactors. Part I: Workflow Development and Case Study for Small LFR District Energy Application

The nuclear industry is developing small reactor designs that can target a variety of deployment locations and energy products. Smaller nuclear designs have traditionally struggled to handle the steep trade-offs between size and cost that have historically incentivized large reactors. This motivates computational optimization of small reactors to minimize costs and quantify the trade-off between size and cost. In this paper, the cost/size trade-off for a small fast reactor is derived using a multi-objective genetic algorithm optimization, with steady-state, transient, and cost analysis of the fast reactor being performed. Specifically, the method is demonstrated on a small 10- to 120-MW(thermal) U-Pu-Zr–fueled lead-cooled fast reactor with a 10-year core life for district energy applications, which can have a thermal load compatible with this range. The results reinforced that fast reactor cores at the lower end of this power range suffer cost penalties due to critical mass considerations. It was found that high power density cores with strong reactivity swings and many control rods were favored over designing to minimize reactivity swing. Furthermore, this contrasts with some traditional configurations designed using engineering judgment and demonstrates that optimizers can find nontraditional but realistic solutions, along with demonstrating the value of incorporating cost functions into whole-reactor design optimization.

Fast reactor↗

Multi-Objective Design Optimization of 100 kW Non-Rare-Earth or Reduced-Rare-Earth Machines

The goal of this project is to reduce the size, weight, cost, and losses associated with rotating electric machinery and its associated power electronics for electric and hybrid vehicle applications. In particular, this effort strives to facilitate electric machinery that will meet the requirements set forth in the USDRIVE Electrical and Electronics Technical Team Roadmap of October 2017. This roadmap calls for an electric machine with a peak power of 100 kW, a continuous rated power of 55 kW, a peak speed of less than 20,000 rpm, a volume of no more than 2 liters, a mass of less than 20 kg, and a useful life of 15 years or 300,000 miles of vehicle service. This will be achieved through a combination of (i) new materials, (ii) new electric machine topologies, (iii) advances in power electronics, and (iv) superior design through the use of formal and rigorous multi-objective optimization-based design founded on advanced analysis techniques.

33 ADVANCED PROPULSION SYSTEMS↗

Optimal Design Approaches for Cost-Effective Manufacturing & Deployment of Chemical Process Families with Economies of Numbers

This work builds on our optimization formulation for process family design and extends it to explicitly include the benefits of economies of numbers. Economies of numbers (sometimes referred to as economies of learning) is a well-documented cost saving phenomenon. It characterizes the manufacturing cost savings due to standardization; in particular, it is capturing the correlation between cost reduction and the number of times a particular product has been manufactured. Following an approach similar to that in Gazzaneo et al. (2022), we develop a costing expression that captures material costs and manufacturing costs as a function of the number of unit modules produced. If the platform has a small number of unit module designs, we will be manufacturing a large number of each of these designs and gaining increased benefits from economies of numbers. However, increasing the number of unit module designs in the platform gives each process variant more choices to consider (at the cost of reducing economies of numbers). The optimization formulation in Stinchfield et al. (2023) pre-specified the number of unit module designs to be included in the platform. Here, by including the economies of numbers explicitly, we allow the mathematical programming formulation to determine the optimal number of unit module designs to include in the platform. We demonstrate this approach on multiple case studies, including MEA-based carbon capture and water desalination.

Stinchfield, Georgia↗

PORFLOW Simulations Supporting Saltstone Disposal Unit Design Optimization

SRNL was requested by SRR to perform PORFLOW simulations to support potential cost-saving design modifications to future Saltstone Disposal Units in Z-Area (SRR-CWDA-2015-00120). The design sensitivity cases are defined in a modeling input specification document SRR-CWDA-2015-00133 Rev. 1. A high-level description of PORFLOW modeling and interpretation of results are provided in SRR-CWDA-2015-00169. The present report focuses on underlying technical issues and details of PORFLOW modeling not addressed by the input specification and results interpretation documents. Design checking of PORFLOW modeling is documented in SRNL-L3200-2015-00146.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗