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At least 127 records · Page 7

Investigation of Superluminescent Diodes for Smart Lighting Systems. Final Report

The solid-state lighting ecosystem has evolved very rapidly over the last few years, with significant improvements in the technical performance of light-emitting diodes (LEDs) and the commoditization of LED-based lighting fixtures. As the performance of conventional lighting products begins to saturate, there is growing market interest in “Lighting as a Service” applications that will leverage advanced systems to impart new functionalities to lighting and improve energy efficiency, human health, and productivity. These “Smart Lighting” systems will include high-performance light sources, specialized sensors, and dynamic controls to deliver high quality, energy efficient, color tunable lighting with customized spatial light delivery and integrated visible light communication capability. To achieve these capabilities, smart lighting systems will place greater demands on the performance of light sources. Highly efficient sources with additional functionalities compared to conventional LEDs, such as small form factor, large modulation bandwidth, and spatially coherent output beams, will be required. While laser diodes have been proposed as potential sources for smart lighting systems, they also exhibit several properties that pose challenges, such as temporal coherence, extremely high spatial coherence, and ultra-narrow linewidths. To address these issues, we propose an investigation of an alternative device architecture known as a superluminescent diode (SLD). SLDs are similar in form to ridge laser diodes and share many of the same characteristics, such as stimulated emission operation, spatially coherent output, small form factor, and the potential for large modulation bandwidth. However, the operating principle for SLDs is distinct from laser diodes in that SLDs lack a strong cavity feedback mechanism, resulting in spatially coherent but temporally incoherent light output. Thus, SLDs may address the issues with laser diodes for lighting, while simultaneously maintaining some of the desirable characteristics of both laser diodes and LEDs. The objectives of this proposal are to design, grow, and fabricate blue (450 nm) SLDs on polar c-plane and nonpolar m-plane free-standing GaN substrates, and to evaluate their potential as sources in smart lighting systems through basic device characterization and detailed investigations of their efficiency droop and modulation bandwidth. The primary scientific aims of this work are to understand the fundamental role of optical gain in the superluminescent (non-lasing) regime on efficiency droop and modulation bandwidth in III-nitride emitters and to understand the effects of higher optical gain on SLD performance by comparing polar c-plane and nonpolar m-plane SLDs. The University of New Mexico (UNM) will collaborate with Sandia National Laboratories (SNL) and the Center for Integrated Nanotechnologies to design, fabricate, grow, and characterize the SLDs. UNM will perform the design and epitaxial growth, while SNL will focus on the fabrication and device characterization. The novelty of the proposed work includes the first comprehensive theoretical and experimental investigations of efficiency droop and the first investigation of modulation bandwidth in GaN-based emitters operating in the superluminescent regime. Moreover, the comparison of c-plane and m-plane SLDs will enable the first analysis of the effects of higher optical gain on the device performance. The development of high-performance GaN-based SLDs may enable efficiency gains and improved functionality in next-generation smart lighting systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Simulation-aided occupant-centric building design: A critical review of tools, methods, and applications

Occupants are active participants in their built environment, affecting its performance while simultaneously being affected by its design and indoor environmental conditions. With recent advances in computer modeling, simulation tools, and analysis techniques, topics such as human-building interactions and occupant behavior have gained significant interest in the literature given their premise of improving building design processes and operating strategies. In practice, the focus of occupant-centric literature has been mostly geared towards the latter (i.e., operation), leaving the implications on building design practices underexplored. This paper fills the gap by providing a critical review of existing studies applying computer-based modeling and simulation to guide occupant-centric building design. The reviewed papers are organized along four main themes, namely occupant-centric: (i) metrics of building performance, (ii) modeling and simulation approaches, (iii) design methods and applications, and (iv) supporting practices and mechanisms. Important barriers are identified for a more effective application of occupant-centric building design practices, including the limited consideration of metrics beyond energy efficiency (e.g., occupant well-being and space planning), the limited implementation and validation of the proposed methods, and the lack of integration of occupant behavior modeling in existing building performance simulation tools. Finally, future research directions are discussed, covering large-scale international data collection efforts to move from generic assumptions about occupant behavior to specific/localized knowledge, improved metrics of measuring building performance, and improved industry practices, such as building codes, to promote an occupant-in-the-loop approach to the building design process.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Semi-Lagrangian nodal discontinuous Galerkin method for the BGK model

In this work, we propose a semi-Lagrangian (SL) nodal discontinuous Galerkin (DG) solver for the BGK equation. The BGK model was introduced by Bhatnagar, Gross, and Krook [1] as a relaxation model for the fundamental Boltzmann equation [5], which describes the kinetic dynamic of rarefied gases with a probability distribution function. The challenges of designing efficient numerical schemes for the Boltzmann equation mainly come from its high dimensionality and complicated nonlinear collision operator. The BGK model gains interests since it has much lower computational cost, due to the relatively simple structure of the relaxation operator in replacement of the collision operator, while simultaneously preserving several important physical properties, such as macroscopic quantities and dissipation of entropy.

97 MATHEMATICS AND COMPUTING↗

Harnessing the power of gradient-based simulations for multi-objective optimization in particle accelerators

Abstract Particle accelerator operation requires simultaneous optimization of multiple objectives. Multi-objective optimization (MOO) is particularly challenging due to trade-offs between the objectives. Evolutionary algorithms, such as genetic algorithms (GAs), have been leveraged for many optimization problems, however, they do not apply to complex control problems by design. This paper demonstrates the power of differentiability for solving MOO problems in particle accelerators using a deep differentiable reinforcement learning (DDRL) algorithm. We compare the DDRL algorithm with model-free reinforcement learning (MFRL), GA, and Bayesian optimization (BO) for simultaneous optimization of heat load and trip rates in the continuous electron beam accelerator facility. The underlying problem enforces strict constraints on both individual states and actions as well as cumulative (global) constraints on energy requirements of the beam. Using historical accelerator data, we develop a physics-based surrogate model which is differentiable and allows for back-propagation of gradients. The results are evaluated in the form of a Pareto-front with two objectives. We show that the DDRL outperforms MFRL, BO, and GA on high dimensional problems.

43 PARTICLE ACCELERATORS↗

Register-Like Storage Block Used as Histograms, Cluster Buffers, and Hough Transform Accumulators for HEP Trigger Systems

In high energy physics experiment trigger systems, block memories are utilized for various purposes, especially in binned searching algorithms. In these algorithms, the storages are demanded to perform like a large set of registers. The writing and reading operation must be performed in single clock cycle and once an event is processed, the memory must be globally reset. These demands can be fulfilled with registers but the cost of using registers for large memory is unaffordable. Another common requirement is the boundary coverage feature during reading process. Additionally, when a memory bin is addressed, the stored contents in the addressed bin and its neighboring bin must be output simultaneously. In this paper, a register-like block storage design scheme is described, which allows updating memory locations in single clock cycle, reading two adjacent bins, and effectively refreshing entire memory within a single clock. The implementation and test results are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Spatiotemporally resolved measurements of electric field around a piezoelectric transformer using electric-field induced second harmonic (E-FISH) generation

When a piezoelectric transformer (PT) is actuated at its second harmonic frequency by a low input voltage, the generated electric field at the distal end can be sufficient to breakdown the surrounding gas, making them attractive power sources for non-equilibrium plasma generation. Understanding the potential and electric fields produced in the surrounding medium by the PT is important for effectively designing and using PT plasma devices. In this work, the spatiotemporally resolved characteristics of the electric field generated by a PT operating in open air have been investigated using the femtosecond electric field-induced second harmonic generation (E-FISH) method. Here, electric field components were determined by simultaneously conducting E-FISH measurements with the incident laser polarized in two orthogonal directions relative to the PT crystal. Results of this work demonstrate the spatial distribution of electric field around the PT’s output distal end and how it evolves as a function of time. Notably, the strongest electric field appears on the face of the PT’s distal surface, near the top and bottom edges and decreases by approximately 70% over 3 mm. The time delay between the PT’s input voltage and measured electric field indicates that there is an about 0.45 phase difference between the PT’s input voltage and output signal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Unified Wireless Charger, On-Board Charger, and Auxiliary Power Module for Electric Vehicle Charging Systems

This paper proposes a unified electric vehicle (EV) charging architecture that integrates wireless power transfer (WPT), an on-board charger (OBC), and an auxiliary power module (APM) within a single architecture. By sharing a multi-functional magnetic structure and active switch bridges, the proposed topology eliminates additional transformers and converter stages, reducing hardware complexity and improving power density. A multipurpose magnetic design achieves magnetic decoupling among the WPT, OBC, and APM functions while maintaining the required coupling for each mode. Through electrical reconfiguration, the WPT operates as an LCC-S converter, whereas the OBC and APM operate as dual-active-bridge (DAB) converters. The system supports multiple operating modes, including simultaneous high-voltage and lowvoltage battery charging. Finite-element and circuit simulations verify the magnetic characteristics and system operation, demonstrating the feasibility of the proposed unified architecture for EV charging applications.

Jo, Cheolhui [ORNL] (ORCID:0000000322692434)↗

Accelerated Aging and Evaluation of Hose-In-Hose Transfer Lines in the Hanford Waste Transfer System - 20312

Nonmetallic materials are used in the United States Department of Energy's Hanford Site Tank Farm waste transfer system. These materials include the inner primary hoses in the hose-in-hose transfer lines (HIHTLs), Garlock{sup R} gaskets, ethylene propylene diene monomer (EPDM) O-rings, and other nonmetallic materials. These nonmetallic materials are exposed to β and γ radiation, caustic solutions as well as high temperature and pressure stressors. How the nonmetallic components react to each of these stressors individually has been well established. However, simultaneous exposure of these stressors has not been evaluated and is of great concern to Hanford Site engineers. Florida International University's Applied Research Center engineers worked closely with key Hanford's Washington River Protection Solutions personnel to develop an experimental test plan that determines how these nonmetallic components react to various simultaneous stressor exposures. In this paper, research on the experimental testing of the hose-in-hose transfer lines used in the Hanford tank farm waste transfer system under simultaneous stressor exposures is presented. The stressor exposure experiments consisted of various combinations of simultaneous stressor exposure of caustic solution, high temperature and high pressure stressors. Research efforts focused on evaluating the aging behavior of EPDM by exposing samples of HIHTLs as well as EPDM dog bone shaped specimens to a 25% NaOH solution at (38 deg. C), operating (54 deg. C) and design temperatures (77 deg. C) for 6 months and 12 months. In addition, HIHTL and the EPDM dog-bone specimens were exposed to only hot water at 77 deg. C for a duration of one year. The mechanical and material properties of the samples were characterized and compared with those of the unexposed samples (baseline). Evaluations included burst pressure tests of the EPDM hose-in-hose transfer lines and material tensile strength test of EPDM dog-bone coupons. Both the tensile strength of the EPDM material dog bones and the burst pressure of the HIHTLs significantly decreased with the increasing temperature and increasing exposure time. When compared with the baseline samples, the burst pressure decreased by 28.75% for the sample aged at 77 deg. C after 12 months, in comparison to sample aged at 38 deg. C and 54 deg. C which had about 1.34% and 5.70% loss in burst pressures, respectively, after 12-month exposure. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Optimizing Heat Recovery with Storage: Control Validation and Sensitivity Analysis of the Time-Independent Energy Recovery Plant Using Modelica

Heat recovery in large building central plants saves energy but traditionally requires simultaneous heating and cooling. The Time-Independent Energy Recovery (TIER) plant shifts this paradigm by integrating thermal energy storage (TES) to enable heat recovery regardless of concurrent demand, offering a highly efficient, space-saving solution to achieve California’s energy goals. However, its integration of heat recovery chillers, cooling-only chillers, cooling towers, and trim air-source heat pumps (ASHPs) creates growing control and sizing complexity. To overcome this, this study employs high-fidelity Modelica dynamic simulation to validate TIER control sequences and optimize equipment sizing. We translated the written Sequences of Operation into executable Control Description Language (CDL) to test logic against sub-hourly loads. This verification workflow successfully identified and resolved critical vulnerabilities, such as thermal storage freezing and equipment short-cycling, in a virtual environment prior to physical deployment. Then, the study analyzes TIER plant performance across three simulated building types in three locations, and a real building load profile, ensuring variety in heating and cooling loads, and simultaneity factors and explores sizing rules for the TES and ASHP capacity. The analysis shows that the TIER plant operates equipment efficiently leading to a plant SCOP of around 7.5 across all scenarios, higher than a traditional ASHP plant, and a viable pathway to de-risk complex system design and control through simulation to identify optimal designs that maximize energy efficiency, minimize operational costs, and ensure robust operation in varied environmental conditions, thereby facilitating the broader adoption of such a solution for large buildings.

Zanetti, Ettore↗

New High-Entropy Perovskite Oxides with Increased Reducibility and Stability for Thermochemical Hydrogen Generation

This project aims to design, synthesize, and test a transformative class of High-Entropy Perovskite Oxides (HEPOs) as redox oxides to enable thermochemical hydrogen generation with improved stability, kinetics, and efficiency. These developed HEPOs are expected to demonstrate improved kinetics with oxygen surface exchange coefficient ( k > 7.5×10 -4 cm/s) in Budget Period (BP) 1, retain its structural stability in a broad range of oxygen non-stoichiometry (Δδ > 0.15) at a low operating reduction temperature of T red < 1400°C in BP 2, and deliver a H 2 yield of over 400 µmol per gram of oxide and high stability with less than 20% degradation after at least 50 cycles in BP 3. This project is feasible due to the unique thermodynamic properties (simultaneously increased reducibility and phase stability) and kinetic characters (stability against particle coarsening and potentially enhanced oxygen transport and surface reaction kinetics) of such HEPOs, and it is enabled by a unique active learning computational design approach. Computational studies have been conducted to investigate the oxygen vacancy formation in complex perovskite systems. * Accurate prediction of V O .. concentration with disordered A-site cations in Fe-based high-entropy perovskite oxides * Combined MC/DFT computation elucidates the mechanism of Co preference on the redox due to the strain introduced by local distortion. In this project, we explored a large number (~150) of perovskite compositions, which are listed in Tables 2 – 4). * All perovskite specimens have been synthesized through a high-throughput high-energy ball milling process, followed by the conventional sintering process. * XRD, SEM/EDS and TGA were performed to confirm the crystal structure, phase homogeneity and oxygen non-stoichiometry for compositionally complex perovskite oxides (CCPOs). * 110 compositions show single-phase from XRD * Unusual aliovalent doping effects in medium-entropy perovskite compositions. * V-shape relation between Δδ vs. x (La 1-x Sr x )(Mn 1/3 Fe 1/3 Ti 1/3 )O 3 * The highest reported hydrogen production for the CCPOs made in this project ( T re = 1350 ºC 30 min, T Ox = 1100 ºC 30 min) * B-site mixing (La 0.8 Sr 0.2 )(Mn 0.2 Fe 0.2 Co 0.4 Al 0.2 )O 3 : 89.97 ± 2.73 mmol H2 /mol oxide (395 ± 10 μmol/g oxide ) (i) No phase transformation during reactions when Co molar ratio is less than 61% (ii) Balance between intrinsic kinetics (oxygen surface exchange) and thermodynamics (oxygen non-stoichiometry) (iii) Preference of Co identified by in-situ XPS * A-site mixing (La 1/6 Pr 1/6 Nd 1/6 Gd 1/6 Ba 1/6 Sr1/6)MnO 3 : 98.48 mmol H2 /mol oxid e (~415 μmol/g oxide )

08 HYDROGEN↗

SymbolNet: neural symbolic regression with adaptive dynamic pruning for compression

Abstract Compact symbolic expressions have been shown to be more efficient than neural network (NN) models in terms of resource consumption and inference speed when implemented on custom hardware such as field-programmable gate arrays (FPGAs), while maintaining comparable accuracy (Tsoi et al 2024 EPJ Web Conf. 295 09036). These capabilities are highly valuable in environments with stringent computational resource constraints, such as high-energy physics experiments at the CERN Large Hadron Collider. However, finding compact expressions for high-dimensional datasets remains challenging due to the inherent limitations of genetic programming (GP), the search algorithm of most symbolic regression (SR) methods. Contrary to GP, the NN approach to SR offers scalability to high-dimensional inputs and leverages gradient methods for faster equation searching. Common ways of constraining expression complexity often involve multistage pruning with fine-tuning, which can result in significant performance loss. In this work, we propose S y m b o l N e t , a NN approach to SR specifically designed as a model compression technique, aimed at enabling low-latency inference for high-dimensional inputs on custom hardware such as FPGAs. This framework allows dynamic pruning of model weights, input features, and mathematical operators in a single training process, where both training loss and expression complexity are optimized simultaneously. We introduce a sparsity regularization term for each pruning type, which can adaptively adjust its strength, leading to convergence at a target sparsity ratio. Unlike most existing SR methods that struggle with datasets containing more than O ( 10 ) inputs, we demonstrate the effectiveness of our model on the LHC jet tagging task (16 inputs), MNIST (784 inputs), and SVHN (3072 inputs).

Tsoi, Ho Fung (ORCID:0000000225502184)↗

Effective design of vibro-impact energy harvesting absorbers with asymmetric stoppers

We report that an investigation is carried out for the purpose of simultaneously controlling a base-excited dynamical system and enhancing the effectiveness of a piezoelectric energy harvesting absorber. Amplitude absorbers are included to improve the energy harvested by the absorber with the possibility of activating broadband resonant regions to increase the operable range of the absorber. This study optimizes the stoppers’ ability for the energy harvesting absorber to generate energy by investigating asymmetric gap and stiffness configurations. Medium stiffnesses of 5 x 10 4 N/m and 1 x 10 5 N/m show significant impact on the primary system’s dynamics and improvement in the level of the harvested power for the absorber. A solo stopper configuration when the gap distance is 0.02m improves 29% in peak power and 9% in average power over the symmetrical case. Additionally, an asymmetric stiffness configuration when one of the stiffnesses is 1 x 10 5 N/m and a gap size of 0.02m indicates an improvement of 25% and 8% for peak and average harvested power, respectively, and the second stopper’s stiffness is 5 x 10 3 N/m. Hard stopper configurations shows improvements with both asymmetric cases, but not enough improvements to outperform the system without amplitude stoppers.

42 ENGINEERING↗

Controlled Pyroshock Test Transients Can Be Used To Better Match Operational Shock Transients and Reduce Artificial Pyroshock Test Failures [Slides]

Shock analysis is typically done via SRS (shock response spectrum). Oftentimes shock analysis is not performed because most loads specifications only supply SRS requirements with no representative shock transients that can be used for analysis. SRS analysis is too conservative. There is no structural dynamics involved as all modes are assumed to have peak responses simultaneously and in-phase with each other. It is possible that all other loads and combination of loads show the design to be good, whereas SRS analysis (1000 g’s are involved) results may require redesign. Multiple shock transients can satisfy a SRS, yet most loads documents don’t provide a representative shock transient that could be used for shock analysis. Shock testing is less common than harmonic and random vibration testing. Engineers typically go into shock tests with very little knowledge of what to expect. A pass/fail type of approach with very little engineering done to prepare for the test or to control the type of shock transient is used. Most engineers will not model the shock test fixture due to lack of knowledge about the details of the test setup. Shock analysis and testing is often an open loop type situation with no test setup modeling, no test correlation, and no control over the test shock transient. In this work, if we can create applied test force transient that comes close to matching calculated force transient then a more reasonable acceleration transient will be created at the test reference accelerometer that better matches operational shocks.

42 ENGINEERING↗

TEAMER: Water Tunnel Data from Testing the Pterofin Skimmer Concept

Pterofin's Skimmer concept relies on a flapping and pitching hydrofoil to extract hydrokinetic energy from water flows. The concept aims to utilize unsteady fluid dynamics phenomena (added mass, shed vorticity, and unsteady boundary layer development) to achieve higher lift coefficients, enabling increased power density of the hydrokinetic device and a fundamental shift in the rpm/torque scaling of the power take off compared with turbines. The Applied Research Laboratory at Penn State, in collaboration with Pterofin, designed and built a proof-of-concept flapping/pitching mechanism which was subsequently tested in ARL's 12-inch water tunnel facility. The mechanical power supplied to or extracted from the mechanism was measured for a range of hydrofoils provided by Pterofin over operating conditions including reduced frequency, Reynolds number, and the ratio between pitching and flapping amplitudes. The power lost to friction in the mechanism was removed from the net power measurement by means of a bare hub tare, with the resultant hydrodynamic power being used to calculate a mechanism-independent and non-dimensional power coefficient. The product of this effort is a dataset describing the power coefficient of a hydrofoil having simultaneous pitching and flapping motions, both of which are approximately sinusoidal. Power coefficients were collected for a range of primary design variables including: - Reduced frequency: 0.01 to 0.95 - Pitching/flapping peak angle ratio: 1.5 to 3.0 - Chord-based Reynolds number: 60,000 to 560,000 Secondary design variables relating to the hydrofoil geometry were explored including: - Aspect ratio - Planform shape - Section thickness distribution - Hydrofoil position relative to the pitching axis - Hydrofoil sweep angle relative to the pitching axis Measured data are provided in mean and time series formats. MATLAB scripts are provided which can be used to generate figures of time-averaged and phase-averaged hydrodynamic power coefficients calculated from the measured data. A complete description of the experiment and data reduction can be found in the Post Access Report for the Pterofin Skimmer test effort which will be available on the TEAMER website. This work was supported by the Pacific Energy Ocean Trust via a TEAMER award.

16 TIDAL AND WAVE POWER↗

Microstructure and mechanical behavior of a TiC nanoprecipitate strengthened V Alloy

The V-4Cr-4Ti (V44) alloys have been proposed as the prime candidate structural material for self-cooled liquid Li blanket and other designs for fusion energy applications. However, the applications of the V44 alloy are limited to a narrow operation temperature window, due to reduction in creep strength at or above 700 °C and susceptibility to irradiation hardening and embrittlement when irradiated below 400 °C. Here, in this work, we explore the feasibility of designing a novel V alloy to form a high number density of TiC nanoprecipitates, in order to simultaneously improve creep strength and provide defect sinks to mitigate irradiation hardening. Computational thermodynamics was used to design a new alloy (V44C) to achieve our goal of high TiC nanoprecipitates density within the alloy V44 matrix. To ensure scalability, the new alloy was made through arc-melting and ingot-casting followed by hot forging, cold rolling and heat treatments of homogenization and precipitation aging. The microstructure was characterized by SEM, TEM, XRD and APT, confirming the existence of nanoprecipitates predicted in the thermodynamic calculations. In addition to microstructural evaluation tensile properties at room temperature and 700 °C, and Charpy impact energy at room temperature were measured. The microstructure and mechanical properties were then compared with those from a historic reference V44 alloy. The tensile strength improvement in V44C was rationalized based on particle and solid solution strengthening mechanism. The fracture behavior was discussed based on the fractography results and necking deformation behavior.

Alloys development↗

Versatile system for ion energy measurements generated by pulsed laser ionization: Insights into electron-ion dynamics

Ion energy distributions generated by pulsed laser interactions with materials are essential for applications ranging from materials science to oncology. Ion energy characterization is particularly important for an emerging mass spectrometry technique called virtual-slit cycloidal mass spectrometry (VS-CMS). The ion energy distribution influences the design and performance of VS-CMS instruments, as well as the efficacy of laser-driven ionization methods in various fields. Several established techniques, including the retarding potential method, time-of-flight (TOF) analysis, and electrostatic energy analyzers, have been employed to measure ion energy distributions. The wide range of ion energies reported highlights the strong dependence of ion energy on laser parameters, target materials, and experimental conditions, as well as the necessity of making independent measurements of the ion energy distribution for specific laser systems and materials. This paper presents the design and characterization of a simple TOF-based apparatus for measuring ion energy distributions from pulsed laser ionization without external fields. This approach minimizes perturbation of electron-ion dynamics and enables simultaneous energy measurements at multiple spatial positions. Here, the apparatus was tested using a nanosecond pulsed Nd:YAG laser operating at 1064 nm, 532 nm, and 266 nm on solid copper sheets at various laser fluences. Simultaneous measurements at different distances provide new insights into ion-electron interactions post-ionization and demonstrate the influence of laser wavelength and fluence on ion energy distributions.

Ion energy↗

Deep Reinforcement Learning Based Volt-VAR Optimization in Smart Distribution Systems

This paper develops a model-free volt-VAR optimization (VVO) algorithm via multi-agent deep reinforcement learning (DRL) in unbalanced distribution systems. This method is novel since we cast the VVO problem in distribution networks to an intelligent deep Q-network (DQN) framework, which avoids solving a specific optimization model directly when facing time-varying operating conditions in the systems. We consider statuses/ratios of switchable capacitors, voltage regulators, and smart inverters installed at distributed generators as the action variables of the agents. A delicately designed reward function guides these agents to interact with the distribution system, in the direction of reinforcing voltage regulation and power loss reduction simultaneously. The forward-backward sweep method for radial three-phase distribution systems provides accurate power flow results within a few iterations to the DRL environment. The proposed method realizes the dual goals for VVO. We test this algorithm on the unbalanced IEEE 13-bus and 123-bus systems. Numerical simulations validate the excellent performance of this method in voltage regulation and power loss reduction.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Application of Sequential Design of Experiments (SDoE) to Large Pilot-Scale Solvent-Based CO2 Capture Process at Technology Centre Mongstad (TCM)

The United States Department of Energy’s Carbon Capture Simulation for Industry Impact (CCSI2) program has developed a framework for sequential design of experiments (SDoE) that aims to maximize knowledge gained from budget- and schedule-limited pilot scale testing. SDoE was applied to the planning and execution of campaigns for testing CO2 capture systems at pilot-scale in order to optimally allocate resources available for the testing. In this methodology, a stochastic process model is developed by quantifying the parametric uncertainty in submodels of interest; for a solvent-based CO2 capture system, these may include physical properties and equipment performance submodels (e.g., mass transfer, interfacial area). This uncertainty is propagated through the full process model, over variable operating conditions, for estimating the resulting uncertainty in key model outputs (e.g., percentage of CO2 capture, solvent regeneration energy requirement). In developing a data collection plan, the predicted output uncertainty is incorporated into an algorithm that seeks simultaneously to select process operating conditions for which the predicted uncertainty is relatively high and to ensure that the entire space of operation is well represented. This test plan is then used to guide operation of the pilot plant at varying steady-state conditions, with resulting process data incorporated into the existing model using Bayesian inference to refine parameter distributions. The updated stochastic model, with reduced parametric uncertainty from data collected, is then used to guide additional data collection, thus the sequential nature of the experimental design. The SDoE process was implemented at the pilot test unit (12 MWe in scale) at Norway’s Technology Centre Mongstad (TCM) in a summer 2018 test campaign with aqueous monoethanolamine (MEA). During the test campaign, the varied operating conditions included the flowrates of circulated solvent, flue gas, and reboiler steam and the CO2 concentration in the flue gas. The process data were used to update probability distributions of mass transfer and interfacial area parameters of a stochastic process model developed by the CCSI2 team. Two iterations of the SDoE process were executed, resulting in the uncertainty in model predicted CO2 capture percentage decreasing by an average of 58.0 ± 4.7% over the full input space of interest. This work demonstrates the potential of the SDoE process for model refinement through reduction in process model parametric uncertainty, and ultimately risk in scale-up, in CO2 capture technology performance.

carbon capture↗