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At least 955 records · Page 53

Integrate FARM with PID controllers: IES Simulation Ecosystem Control System Development

The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM was designed to support the HERON software module in the solution of the optimal dispatch problem for IES units. As the result of HERON-FARM dispatch simulation, the set-point trajectories are optimized to meet constraints on both the production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and the process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.) at a coarse time resolution (every 10 or 100 seconds) over long time horizons (several days or weeks). In case the operational constraints need to be met at finer time resolution, the computational burden of HERON-FARM would linearly increase with the sampling rate, and sub-optimal solutions might be obtained. System responses characterized by overshoots and damped oscillations temporarily violating the imposed constraints might occur during abrupt power transients. In this report, a hierarchical control system architecture for the operation of the Dynamic Energy Technology and Integration Laboratory (DETAIL) facility constructed at INL was proposed. First, the preliminary studies on the proposed control strategy for operating the facility and the designed PI controllers were reviewed. In particular, the current approach for generating the set-point trajectories was studied, and its limits were identified. To this aim, the inclusion of a Supervisory Control layer embedding a modified version of the FARM algorithm for preserving the system safe operation over both long and real-time horizons was proposed. In this way, FARM would be applied twice, i.e., the original version (“FARM Validator”) aiding the solution of the power dispatch problem, and the modified version (“FARM Supervisory” coordinating the PI controllers to address the real-time control tasks. Despite the kernel of the two modules is the same algorithm, their roles, tasks, and capabilities are quite different. A detailed description of the role of FARM at addressing low-level control tasks is provided, along with tentative operational procedures for training the models embedded into the algorithm by using the collected experimental data.

42 ENGINEERING↗

Resolving Electron Injection from Singlet Fission-Borne Triplets into Mesoporous Transparent Conducting Oxides

Photoinduced electron transfer from a molecular chromophore into mesoporous metal oxide substrates occurs efficiently from both singlet and triplet excited states for traditional metal-to-ligand charge transfer (MLCT) dyes. All organic molecules that undergo singlet fission (SF), the process of generating two triplet excitons with photoexcitation of one singlet exciton, offers a promising method of generating two charges per one absorbed photon. However, the singlet-triplet energy balance required to drive SF often places the driving force for triplet electron injection into metal oxides too low. As such, the dynamics of singlet vs. triplet electron transfer for SF in dye-sensitized solar cell configurations has not been elucidated. Here, we use applied bias transient absorption spectroscopy to modulate the driving force for triplet electron transfer from an anthradithiophene-based SF chromophore (ADT-COOH) adsorbed to mesoporous indium tin oxide (nanoITO).

CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SU↗

MIP dQ/dx Calibration in DUNE ND-LAr Prototypes with Pixelated Charge Readout

The Deep Underground Neutrino Experiment (DUNE) will be a next-generation long baseline neutrino oscillation experiment that will employ LArTPC technology in a near detector placed at Fermilab and a far detector at the Sanford Underground Research Facility, at a baseline of 1300 km. The DUNE Liquid Argon Near Detector (ND-LAr) design takes into account the high neutrino intensity expected from the beam at the Long-Baseline Neutrino Facility (LBNF): 35 modules, each containing two optically separated time projection chambers, are instrumented with a pixel-based, true 3D charge readout alongside scintillation light traps to disentangle the O(100) interactions expected per 10us beam spill. A robust prototyping program supports ND-LAr’s design: the 2x2 Demonstrator consists of four scaled-down ND-LAr modules exposed to the NuMI beam at Fermilab, and the Full Scale Demonstrator (FSD) is a single ND-LAr module tested with cosmic rays at the University of Bern. We present here an analysis of minimum ionizing particle (MIP) tracks selected from 2x2 beam data and FSD cosmic ray data used to benchmark the pixel-based charge readout simulation and calibration in both detectors, with the ultimate goal of validating the design of DUNE ND-LAr as well as informing future calibration methods. This poster will showcase the dependence of the charge response on track inclination as well as a per-pixel dQ/dX extraction.

Mandujano, Roberto [UC, Irvine]↗

A Study of Propane Combustion in a Spark-Ignited Cooperative Fuel Research (CFR) Engine

Liquefied petroleum gas (LPG), whose primary composition is propane, is a promising candidate for heavy-duty vehicle applications as a diesel fuel alternative due to its CO 2 reduction potential and high knock resistance. To realize diesel-like efficiencies, spark-ignited LPG engines are proposed to operate near knock-limit over a wide range of operating conditions, which necessitates an investigation of fuel-engine interactions that leads to end-gas autoignition with propane combustion. This work presents both experimental and numerical studies of stoichiometric propane combustion in a sparkignited (SI) cooperative fuel research (CFR) engine. Engine experiments are initially conducted at different compression ratio (CR) values, and the effects of CR on engine combustion are characterized. A three-pressure analysis (TPA) model based on the two-zone combustion concept is developed in GT-Power and validated using test results to estimate in-cylinder wall temperatures, residual gas fraction, etc. This model is further utilized to examine end-gas chemistry by enabling the SI turbulent flame combustion and unburned gas chemical kinetics modules. Finally, a three-dimensional (3D) computational fluid dynamic (CFD) model of the CFR engine is developed in CONVERGE, where the G-equation and SAGE detailed chemical kinetics models are implemented for combustion modeling. Here, a 153 species reduced chemical kinetics mechanism derived from the detailed NUIGMech1.1 mechanism based on the ignition delay and laminar flame speed (LFS) studies is used to generate an LFS lookup table and to describe end-gas autoignition chemistry. Multi-cycle Reynolds-averaged Navier-Stokes (RANS) simulations are then performed for the tested CRs, and the numerical model is shown to be capable of predicting the propane combustion characteristics, particularly the end-gas autoignition behavior.

20 FOSSIL-FUELED POWER PLANTS↗

NMPC for Mode-Switching Operation of Reversible Solid Oxide Cell Systems

Solid oxide cells (SOCs) are a promising dual-mode technology that generates hydrogen through high-temperature water electrolysis and generates power through a fuel cell reaction that consumes hydrogen. Reversible operation of SOCs requires a transition between these two modes for hydrogen production setpoints as the demand and price of electricity fluctuate. Moreover, a well-functioning control system is important to avoid cell degradation during mode-switching operation. In this work, we apply nonlinear model predictive control (NMPC) to an SOC module and supporting equipment and compare NMPC performance to classical proportional integral (PI) control strategies, while ramping between the modes of hydrogen and power production. While both control methods provide similar performance in many metrics, NMPC significantly reduces cell thermal gradients and curvatures (mixed spatial-temporal partial derivatives) during mode switching. A dynamic process flowsheet of the reversible SOC system was developed in the open-source, equation-based IDAES modeling framework. Our IDAES dynamic simulation results show that NMPC can ramp the SOC system between hydrogen and power production targets within short mode-switching times. Moreover, NMPC can comply with operating limits in the SOC system more effectively than PI, and only NMPC can directly enforce user-specified limits for mixed spatial-temporal partial derivatives of temperature. This allows for management of the trade-off be-tween operating efficiency and cell degradation, which is dependent on these temperature curvatures.

Li, Mingrui↗

Systems and methods for controlling an industrial asset in the presence of a cyber-attack

Systems and methods are provided for the control of an industrial asset, such as a power generating asset. Accordingly, a cyber-attack model predicts a plurality of operational impacts on the industrial asset resulting from a plurality of potential cyber-attacks. The cyber-attack model also predicts a corresponding plurality of potential mitigation responses. In operation, a cyber-attack impacting at least one component of the industrial asset is detected via the cyber-attack neutralization module and a protected operational impact of the cyber-attack is identified based on the cyber-attack model. The cyber-attack neutralization module selects at least one mitigation response of the plurality of mitigation responses based on the predicted operational impact and an operating state of the industrial asset is altered based on the selected mitigation response.

D'Amato, Fernando Javier↗

Machine-Learned Force Field for Molecular Dynamics Simulations of Nonequilibrium Ammonia Synthesis on Iron Catalysts

Ammonia (NH 3 ) is one of the most important industrial chemicals. The conventional NH 3 synthesis method-the Haber–Bosch process-converts atmospheric nitrogen (N 2 ) into NH 3 using H 2 with an iron (Fe) catalyst. However, this process requires high pressures (100–200 atm) and temperatures (700–800 K) near thermal equilibrium. Recently, Fe-based nanocatalysts have been reported to produce promising NH 3 yields under atmospheric pressures and temperature-modulated nonequilibrium conditions. Understanding the mechanism of nonequilibrium catalysis with programmed temperature variation could help to optimize this fully electrified and less energy-intensive process. Although reactive molecular dynamics (RMD) simulations can be a useful tool to model nonequilibrium catalytic processes, they require the development of accurate force fields (i.e., interatomic potentials). Here, we present a machine-learned (ML) force field within the Deep Potential MD (DPMD) framework, trained using periodic density functional theory (DFT) calculations, to model NH 3 synthesis on Fe catalysts with various surface adsorbates such as *N, *H, *N 2 , *H 2 , *NH, *NH 2 , and *NH 3 . Here, we generated the DFT data from static models of elementary reactions on the most stable (110) surface of body-centered cubic Fe, which then were augmented by data from constant number of particles–volume–temperature (NVT) DFT-MD trajectories at various temperatures. Finally, we utilized the fully optimized ML force field to investigate reaction dynamics at an Fe(110) surface at linearly increasing temperatures using NVT-DPMD simulations. Our simulations indicate that pulsed temperature ramping could prove favorable for NH3 synthesis. For example, we conducted ramping under multiple sets of conditions: (i) from 900 to 1200 K over periods of 0.1–0.3 ns for Fe surfaces precovered with N or NH along with H; and (ii) from 300 to 600 K over 0.1–0.3 ns for Fe surfaces precovered with NH 3 . While our simulations so far are limited to short time scales (very rapid heating), these observations shed light on the mechanism of the high NH 3 synthesis rate achieved in a novel temperature-modulated nonequilibrium catalytic reactor using pulsed heating and cooling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nonlinear model predictive control for mode‐switching operation of reversible solid oxide cell systems

Abstract Solid oxide cells (SOCs) are a promising dual‐mode technology for the production of hydrogen through high‐temperature water electrolysis, and the generation of power through a fuel cell reaction that consumes hydrogen. Switching between these two modes as the price of electricity fluctuates requires reversible SOC operation and accurate tracking of hydrogen and power production set points. Moreover, a well‐functioning control system is important to avoid cell degradation during mode‐switching operation. In this article, we apply nonlinear model predictive control (NMPC) to an SOC module and supporting equipment and compare NMPC performance to classical proportional‐integral (PI) control strategies, while switching between the modes of hydrogen and power production. While both control methods provide similar performance across various metrics during mode switching, NMPC demonstrates a significant advantage in reducing cell thermal gradients and curvatures (mixed spatial‐temporal partial derivatives), thereby helping to mitigate long‐term degradation.

08 HYDROGEN↗

Long-range optical coupling with epsilon-near-zero materials

Long-range resonant quantum tunneling of electrons happens across potential barriers when the wavefunction interferes constructively outside the barrier. Here we demonstrate an analogy in optical systems based on epsilon-near-zero materials, achieving phase-modulated, long-range optical interactions between transparent semiconducting oxide layers beyond the evanescent photonic coupling. Distinct from weak thin-film interference, intense electromagnetic fields confined within the epsilon-near-zero thin films show anti-correlated intensity oscillations as a function of interlayer separation up to hundreds of microns. The oscillatory, anti-correlated electromagnetic field intensities were probed by second harmonic generation from wedged indium tin oxide multilayers. Such a system that hosts subwavelength mode footprint and simultaneously long-range radiative coupling offers prospects for long-distance optical communication, large-scale photonic circuits, and hybrid quantum photonic systems.

Wang, Danqing [Fudan University, Shanghai (China);↗

The quantitative genetics of gene expression in Mimulus guttatus

Gene expression can be influenced by genetic variants that are closely linked to the expressed gene (cis eQTLs) and variants in other parts of the genome (trans eQTLs). We created a multiparental mapping population by sampling genotypes from a single natural population of Mimulus guttatus and scored gene expression in the leaves of 1,588 plants. We find that nearly every measured gene exhibits cis regulatory variation (91% have FDR < 0.05). cis eQTLs are usually allelic series with three or more functionally distinct alleles. The cis locus explains about two thirds of the standing genetic variance (on average) but varies among genes and tends to be greatest when there is high indel variation in the upstream regulatory region and high nucleotide diversity in the coding sequence. Despite mapping over 10,000 trans eQTL / affected gene pairs, most of the genetic variance generated by trans acting loci remains unexplained. This implies a large reservoir of trans acting genes with subtle or diffuse effects. Mapped trans eQTLs show lower allelic diversity but much higher genetic dominance than cis eQTLs. Several analyses also indicate that trans eQTLs make a substantial contribution to the genetic correlations in expression among different genes. They may thus be essential determinants of “gene expression modules,” which has important implications for the evolution of gene expression and how it is studied by geneticists.

59 BASIC BIOLOGICAL SCIENCES↗

Power Electronics Manufacturing Improvements for Heavy-Duty Fuel Cell Vehicles

The Marel Power Solutions project, funded by the U.S. Department of Energy under Award DE-SC0023801, focused on advancing manufacturing techniques for power electronics in heavy-duty fuel cell vehicles. The research aimed to enhance system efficiency, reduce costs, and support broader adoption of hydrogen fuel cell technology. Key areas of investigation included power topology, thermal modeling, system architecture, and accessibility through software tools. Key Accomplishments: 1. Power Topology: - Developed an interleaved boost converter with optimized phase count, leveraging Marel’s proprietary Power Stacks. - Achieved reduced parasitic inductance and resistance, enabling high efficiency in DC-DC converters. 2. Thermal Modeling: - Integrated innovative cooling systems into compact Silicon Carbide (SiC) modules. - Simulations demonstrated the ability to dissipate significant heat (up to 7.5 kW), ensuring device reliability under heavy loads. 3. System Architecture: - Utilized simulation tools to analyze the impact of various fuel cell and vehicle parameters on efficiency. - Highlighted the role of smaller, modular improvements, such as enhanced DC-DC converters, in achieving system-wide gains. 4. Accessibility: - Evaluated and implemented MATLAB/Simulink code generation tools for real-world hardware applications. - Demonstrated the potential for rapid prototyping of custom power systems with reduced development costs. Impact and Benefits: - Efficiency and Cost Reduction: Marel’s cooling technology enhances SiC die performance, reducing the number of dies required and overall system size. - Scalability and Flexibility: The innovations support tailored solutions for diverse applications, from mass transit to mining vehicles. - Sustainability: The research promotes the integration of electrification technologies, helping meet rising energy demands sustainably. Conclusion: The project’s outcomes advance the state of power electronics for hydrogen fuel cell vehicles, enabling more efficient, compact, and cost-effective solutions. These developments lay a foundation for future innovation, contributing to the broader adoption of clean energy technologies in transportation and other industries.

08 HYDROGEN↗

Novel Algae Technology for CO2 Utilization

The United States, the world’s largest energy user and second largest CO2 emitter, is heavily dependent on fossil energy. In 2014, U.S. coal burning utilities emitted ~1562 million (MM) tons/year (TPY) of CO2 into the atmosphere, accounting for 76% of the total US power sector emissions1. Hence, reducing the CO2 emission footprint from coal plants is widely viewed as a key element in mitigating global warming. Despite significant interest, implementation of CO2 capture technologies has been constrained by the high capture cost which significantly increases the total cost of electricity. Not only is capturing CO2 with traditional technologies expensive, but generally the CO2 has little value and additional expense must be incurred for sequestration. This project funded by a SBIR grant from the U.S. D.O.E. to Helios-NRG in collaboration with the State University of New York at Buffalo (UB) and Membrane Technology and Research Inc. (MTR) aimed to develop a novel, algae based technology to capture CO2 from the effluent of coal-based power plants and convert it to renewable bio-fuels and higher value co-products such as animal feed and nutraceuticals with the potential to enable a substantial reduction in the net cost of carbon capture. The Phase 2 project was aimed at further demonstrating the technical feasibility of the proposed multi-stage continuous (MSC) flow CO2 capture system and the generation of high-value co-products to offset the CO2 capture cost. The project was completed and the project objectives were met and exceeded. A first-of-a-kind integrated, laboratory scale MSC process unit was fabricated and tested in a greenhouse. The tests were conducted with the preferred algae species identified in Phase I and simulated flue gas containing contaminants at levels typically present in the post flue gas desulfurization (FGD) stream, including ~12% CO2, acid gas (SOX, NOX), and a large number of heavy metals. The tests were successful and demonstrated a 25g/m2/day seasonal average algae productivity and an 80% CO2 capture efficiency. Two new algae species were identified for high-value nutraceutical production. Studies to improve growth rate and nutraceutical content of these algae species were performed and a pathway for further improvements was identified. A new dewatering technology called DeAqua was further advanced. Significant improvement in the performance index was achieved. The anti-fouling membrane was developed and fabricated into a module. The fabricated membrane module was tested with algae slurry and demonstrated improved fouling resistant properties, that can potentially reduce the cost and energy of the critical dewatering step. Test data were used to simulate operation of the overall process. The preliminary economic analysis was updated and modelled based on a 5000-acre algae farm. To the extent possible, the financial and operating assumptions used were the same as those used in the DOE’s 2022 projections for algae technology for CO2 capture and utilization. The results showed the proposed technology’s potential to significantly reduce the cost of CO2 capture compared to current options and that the high value products generated from the CO2 captured can make a step change in the cost of carbon capture. Plans to advance the technology to Phase 2B were developed and potential end-user partners were identified.

Maloney, James↗

High‐Concentration Alcohol Generation in Bipolar Membrane CO Electrolyzer

Electrochemical reduction of carbon dioxide and carbon monoxide offers an electricity‐powered route to make multicarbon liquid products. However, in conventional systems employing anion exchange membranes (AEMs), significant liquid product crossover leads to dilute product streams, increasing separation costs; and also produces unwanted anodic oxidation, further decreasing overall efficiency. Here, we report a forward‐biased bipolar membrane (FB‐BPM) system that achieves <10% liquid product crossover while sustaining a highly alkaline environment near the cathode, suppressing ethylene and hydrogen and favoring liquid products. By tuning catalyst composition to modulate the adsorption of *H and *OH, we steer selectivity toward acetate and alcohols. Using the FB‐BPM system, we achieve >25 wt% acetate on CuZn and >15 wt% alcohols on CuSn directly from the cathode outlet stream.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bacterial microcompartments as a next-generation metabolic engineering tool: utilizing nature's solution for confining challenging catabolic pathways

Advancements in synthetic biology have facilitated the incorporation of heterologous metabolic pathways into various bacterial chassis, leading to the synthesis of targeted bioproducts. However, total output from heterologous production pathways can suffer from low flux, enzyme promiscuity, formation of toxic intermediates, or intermediate loss to competing reactions, which ultimately hinder their full potential. The self-assembling, easy-to-modify, protein-based bacterial microcompartments (BMCs) offer a sophisticated way to overcome these obstacles by acting as an autonomous catalytic module decoupled from the cell's regulatory and metabolic networks. More than a decade of fundamental research on various types of BMCs, particularly structural studies of shells and their self-assembly, the recruitment of enzymes to BMC shell scaffolds, and the involvement of ancillary proteins such as transporters, regulators, and activating enzymes in the integration of BMCs into the cell's metabolism, has significantly moved the field forward. These advances have enabled bioengineers to design synthetic multi-enzyme BMCs to promote ethanol or hydrogen production, increase cellular polyphosphate levels, and convert glycerol to propanediol or formate to pyruvate. These pioneering efforts demonstrate the enormous potential of synthetic BMCs to encapsulate non-native multi-enzyme biochemical pathways for the synthesis of high-value products.

59 BASIC BIOLOGICAL SCIENCES↗

Toward extreme high-temperature supercritical CO 2 power cycles: Leakage characterization of ceramic 3D-printed heat exchangers

We report future supercritical carbon dioxide (sCO 2 ) Brayton power cycles demand high-performance gas-to-gas heat exchangers (HXs) operating under extreme temperature and pressure conditions at which most existing superalloy materials fail to function safely. Ceramic HXs are deemed excellent candidates for advanced sCO 2 power plants as they can withstand high-temperature working environments. Particularly, ceramic 3D printing enables compact HX topologies employing complex and efficient heat transfer features. However, ceramic 3D-printed walls separating hot and cold flow streams are susceptible to a through-plane leakage inherent to a powder-based manufacturing process, including ceramic 3D printing. A potential leakage through ceramic separating walls poses a significant challenge in developing reliable ceramic 3D-printed HXs and could deteriorate thermal performance. In this study, various parameters, including feedstock slurry, 3D-printing direction, and post-processing conditions, are considered, for the first time, to characterize the argon gas leakage rate associated with alumina 3D-printed parts. Three 3D-printed ceramic structures of flat plates, curved tubes, and small-scale plate-and-frame HXs with various thicknesses are systematically studied to determine powder and ceramic 3D-printing conditions to eliminate the through-plane leakage. The results showed that an alumina 3D-printed plate with a thickness of 0.75 mm demonstrates a permeability of 6 x 10 -4 milli-darcy. An alumina 3D-printed tube with a wall thickness of 0.9 mm revealed a permeability of 9.6 x 10 -7 milli-darcy. Furthermore, leakage test results of functional 3D-printed modules showed a dependency on the 3D-printing direction. Particularly, alumina cell-scale HXs employing 1.5-mm-thick horizontal and vertical 3D-printed separating walls demonstrated impermeability and gas permeability of 7.2 x 10 -5 millidarcy, respectively. Insights gained from the present study facilitate the development of complex ceramic 3D-printed HXs and other balance of plant components for next-generation high-temperature high-pressure sCO 2 power cycles.

36 MATERIALS SCIENCE↗

Zinc chloride affects chondrogenesis via VEGF signaling

Highlights: • ZnCl2 increases expression of various chondrogenic signaling intermediates. • VEGF/VEGFR play a key role in modulating levels of chondrogenesis. • Insulin mimetics are an appealing option for improvement of fracture healing. • Axitinib + ZnCl2 treatment results in decreased transcription of chondrogenic genes. Insulin mimetics, including zinc containing compounds, have previously been shown to influence chondrogenesis as it relates to healing of fractures in various preclinical models. However, the mechanism by which these compounds drive chondrogenic differentiation is yet undefined. Here, via next-generation sequencing (NGS) and in vitro functional validation, we show that Zinc Chloride (ZnCl{sub 2}) induces expression of both chondrogenic genes (Sox9, Runx1, collagen) as well as genes associated with VEGF-mediated signal transduction, including VEGF receptors 1 and 2 and their ligands; VEGF-A and VEGF-B. Noticeably, although insulin was able to also induce expression of these pro-angiogenic and pro-chondrogenic genes, the impact of insulin on expression of VEGF receptor and ligand genes was marginal when compared to that of ZnCl{sub 2.} Furthermore, while the VEGFR antagonist, Axitinib, was able to attenuate the pro-chondrogenic effects of both insulin and ZnCl{sub 2}; a reduction in gene and protein expression was most profoundly observed when the antagonist was applied to cells treated with ZnCl{sub 2.} Taken together, these data suggest an important role for the VEGF-mediated signal transduction pathways in the positive effects observed when applying zinc-based compounds as adjuvants for chondrogenesis-mediated fracture healing. In this regard, further mechanistic evaluation of ZnCl{sub 2} and other zinc-containing insulin mimetics may support rational design of therapies targeted for disease indications associated with impaired fracture healing.

60 APPLIED LIFE SCIENCES↗

High-order ( N = 4–6) multiphoton absorption and mid-infrared Kerr nonlinearity in GaP, ZnSe, GaSe, and ZGP crystals

We report a study of high-order multiphoton absorption, nonlinear refraction, and their anisotropy in four notable mid-infrared χ (2) crystals: GaP, ZnSe, GaSe, and ZGP using femtosecond pulses at 2.35 μm with peak intensity in excess of 200 GW/cm 2 . We found that the nonlinear absorption obeys a perturbation model with multiphoton absorption (MPA) orders from N = 4–6, in agreement with the bandgaps of the crystals. A study of the role of free carrier absorption, performed by changing the pulse duration from 30 to 70 fs while maintaining a constant peak intensity, showed that, at our intensity levels, free carriers generated during the MPA process absorb much more strongly than would be expected from their known linear absorption cross section. Possible mechanisms for this anomalous behavior are high-field effects, such as intravalley scattering in the conduction band and absorption to higher lying bands. Nonlinear refractive indices were measured using (i) closed aperture Z-scan and (ii) spectral broadening due to self-phase modulation, both methods agreeing with each other.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Highly Available Nuclear Power for Mission-Critical Applications

Some energy consumers require power on an anytime, all-year-round basis with a high level of certainty, including defense installations, isolated communities, and some industrial processes. For these customers, interruptions in electricity or heat can mean substantial financial loss or even loss of life. In the absence of grid-scale energy storage, a high level of power availability can be accomplished only through the robustness and redundancy of power generators. The NuScale small modular reactor design is well suited to provide highly available power because of several features related to both the nuclear steam supply system and the overall plant design. In analogy to Redundant Array of Independent Disks (RAID) systems used to provide highly reliable data storage, a NuScale plant can assure sustained power generation by virtue of its Redundant Array of Integral Reactors (RAIR).This paper describes the NuScale RAIR plant features and summarizes the results of a rigorous analysis of RAIR availability as a function of power or, conversely, the RAIR plant output power as a function of power availability. The analysis utilized the Matrix Laboratory code (MATLAB) and included probability distributions for the frequency and duration of module outages due to planned and unplanned events. Further, the study evaluated the impact of implementing turbine bypass rather than module shutdown and using one or more modules to supply house loads in the case of loss of off-site power (LOOP). Availability results are presented for a 12-module RAIR plant with and without turbine bypass enabled during a LOOP and for different possible connections to the off-site power distribution grid and dedicated service loads. Results indicate that a very high level of availability can be achieved at relatively high power output levels, regardless of turbine bypass and dedicated load connection, compared to the operating fleet.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗