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At least 451 records · Page 25

Analysis of PNAR Spent Fuel Safeguards Measurements using the ORIGEN Data Analysis Module

This paper summarizes the analysis of the Passive Neutron Albedo Reactivity (PNAR) measurements using the ORIGEN data analysis module for 23 boiling water reactor spent fuel assemblies that were performed in Finland under an international collaboration on spent fuel safeguards verification methods. PNAR is part of the proposed integrated nondestructive system to be used for safeguards verifications at the planned Finnish encapsulation facility. Besides measuring passive neutron and gamma emission rates from an assembly like a Fork detector, PNAR also measures the PNAR ratio, which is expected to correlate with the fissile content in the assembly. The emission rates and PNAR ratio can be used to verify the operator declarations and the fissile content of an assembly, respectively. The analysis was performed using the ORIGEN Data Analysis Module, which was originally developed for predicting Fork detector neutron and gamma signals for spent fuel measurements and has been integrated into the Integrated Review and Analysis Package developed by Euratom and the IAEA. The Module includes the ORIGEN burnup analysis code and integrates detector response functions pre-generated using MCNP to predict detector signals in several seconds per assembly. In this study, new response functions specific to PNAR measurements were generated for ORIGEN Module. The study also analyzes impacts of using detailed fuel design and operation information vs. standard safeguards information on results calculated by ORIGEN Module. Using detailed information reduced the standard deviation of relative differences between calculated and measured neutron count rates among the 23 assemblies from ~10% to ~4%. The results obtained using standard safeguards information for these PNAR measurements were similar to those obtained for the Fork detector. A clear trend was found between the calculated net neutron multiplications and the measured PNAR ratios of the 23 assemblies. This paper describes how ORIGEN Module calculates the expected PNAR neutron and gamma signals and PNAR ratio and how they compare with corresponding measured values.

Ilas, Germina↗

In-Package Common-Mode Filter for GaN Power Module with Improved Radiated EMI Performance

This paper discusses the impact of parasitic inductances on the electromagnetic interference (EMI) performance at radiated frequency and provides a new concept for high-frequency wide bandgap (WBG) power module package design with integrated π-type common mode filter (π-CMF). The connection parasitic-inductances of a π-type CMF model are analyzed, and the parasitic inductances from the CMF to the CM noise source and to the heatsink are minimized to improve the CMF's EMI performance in the radiated frequency range. Therefore, placing the π-CMF closer to the power module (i.e. in-package CMF) provides a larger noise attenuation compared to placing it outside the module (i.e. external CMF). To verify the theoretical analysis, a half-bridge GaN power module with an in-package π-CMF is designed, and experiments are conducted by comparing the attenuated noise spectrums of a 70-V/1.75-A hard-switching buck converter built by the designed module with an external CMF and the power-module integrated CMF. According to the experiment results, up to 10 dBμV more attenuation is achieved by the in-package CMF than the external CMF, validating the analytical conclusion.

Xue, Lincoln↗

Development of MCNP Training Modules for Safeguards Practitioners [Abstract]

The Monte-Carlo N-Particle (MCNP) software developed at LANL is the most widely used neutron transport code in the world. It is an essential tool for a variety of applications including detector development and design, nuclear fuel burnup simulation, criticality safety, and nondestructive assay system optimization. For this reason, it is indispensable within the safeguards and materials control & accountability (MC&A) communities. Multiple MCNP training courses have been created and taught over the last several decades by the MCNP development team at LANL, however there are no existing courses that cover specialized topics considered fundamental to NDA and safeguards models. To fill this gap, the MCNP team and Safeguards Science and Technology group at LANL have co-created a set of training modules customized to meet the specialized needs of the safeguards and MC&A communities. The basic modules cover concepts such as NDA system optimization, He-specific and other capture tallies, and tools for improved theoretical understanding. An advanced module was also created to cover topics including variance reduction for active interrogation simulations, use of the LANL MCNPTools post-processor, PTRAC (particle tracking) and list-mode data simulations, and fuel burnup simulations. The training modules teach to the latest and most state-of-the-art MCNP features and tools released by the development team at LANL and are intended to be taught jointly by the developers and safeguards experts. Ultimately, we hope that creation of these modules will serve to capture and convey the safeguards modeling and MCNP expertise at LANL, and that we will be able to share the modules more broadly with the MC&A and safeguards communities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

In-situ I-V measurement of a module in a PV array

In one respect, disclosed is an in-situ current-voltage (I-V) measurement device for photovoltaic modules in a photovoltaic array, comprising a variable load, wherein the variable load is configured to be connected in parallel with a module, wherein the module is connected in series with at least one other module in a string, such that the module supplies current simultaneously to the string and to the variable load, and wherein the variable load is controlled by a controller, and wherein the controller is configured to shift an I-V operating point of the module, based at least upon varying the variable load.

Gostein, Michael↗

Mathematics Integrated with Computer Science through Scratch: Curricular Modules for the Middle Grades

A project funded by the National Science Foundation, Computer Science Integrated with Mathematics in Middle Schools (CSIMMS) (DRL-1640039), brought middle-school mathematics teachers together with university computer science (CS) faculty and STEM education faculty to design, develop, and test curriculum modules in which CS is integrated into instruction for middle-school general-mathematics courses. The project developed integrated math/CS curriculum modules (for grades 6, 7, and 8), complete with student tasks and teacher materials to guide classroom implementation. Across the project, sixteen teachers from four middle schools representing different school contexts (both urban and suburban, serving students from a range of demographic and socioeconomic backgrounds) participated as members of the design team and trial testers of the math/CS modules. All modules underwent multiple years of testing and refinement, with extensive input from the teachers who co-designed and implemented them. Approximately 50-100 middle-school students participated in the classes of those who taught each year. The modules in this volume feature a range of models for integrating mathematics and computer science at the 6th and 7th grade levels. All modules foreground the teaching of grade-level mathematics content, with computer science functioning to motivate and/or reinforce these ideas.

Andrews larson, Christine↗

Double-Side Cooled 1.2kV, 300A SiC MOSFET Phase-leg Modules for 200 kW, > 100 kW/L Traction Inverters

The packaging of a double-side cooled 1.2 kV, 149 A SiC phase-leg modules has been reported in recent years for making 100 kW, 100 kW/L traction inverters. Each phase-leg module consists of two SiC MOSFETs, one per switch position. Six of the phase-leg modules are assembled into a segmented inverter configuration to meet the power and power density requirement. In this work, the layout of the phase-leg module was redesigned to include four of the SiC MOSFETs, two per switch position, with the aim of doubling the power to 200 kW and increasing the power density beyond 100 kW/L, but with only a 10.25% footprint increase. Key features of the packaging technology developed in the previous work were implemented in the current work, which include silver sintering for chip bonding and porous silver inter-posts for bonding device source pads to substrate. Parasitic extraction simulation showed that the four-chip module has a low parasitic inductance of 4.7 nH, like the two-chip module. Static characterization of the four-chip prototypes showed a low average on-resistance of 9 mΩ and a low average leakage current of 5 nA at Vds of 1.2 kV.

Zhang, Zichen↗

Experimental Validation of a Module Cell Cracking Model

The What's Cracking app can predict how changes in crystalline silicon photovoltaic (PV) module materials, design, and mounting affect its susceptibility for cell fracture under uniform loading. This work has experimentally validated the app. A set of commercial crystalline silicon PV modules was obtained for this study. The modules were uniformly loaded at three different mounting points, and their subsequent cell fractures were recorded. A large sample size allowed for the development of an experimental statistical model for cell fracture. Here, the comparison of the experiment to predictions from the app is in excellent agreement. Both experimental and modeling results also elucidate how moving the module mounting points toward the center of the module increases the probability of cell fracture.

14 SOLAR ENERGY↗

Accumulate Repeat Accumulate Coded Modulation

In this paper we propose an innovative coded modulation scheme called 'Accumulate Repeat Accumulate Coded Modulation' (ARA coded modulation). This class of codes can be viewed as serial turbo-like codes, or as a subclass of Low Density Parity Check (LDPC) codes that are combined with high level modulation. Thus at the decoder belief propagation can be used for iterative decoding of ARA coded modulation on a graph, provided a demapper transforms the received in-phase and quadrature samples to reliability of the bits.

coded modulation↗

Solvent–free Synthesis of Multi–Module Pore–Space–Partitioned Metal–Organic Frameworks for Gas Separation

Multi-module design of framework materials with multiple distinct building blocks has attracted much attention because such materials are more amenable to compositional and geometrical tuning and thus offer more opportunities for property optimization. Few examples are known that use environmentally friendly and cost-effective solvent-free method to synthesize such materials. Here, we report the use of solvent-free method (also modulator-free) to synthesize a series of multi-module MOFs with high stability and separation property for C 2 H 2 /CO 2 . The synthesis only requires simple mixing of reactants and short reaction time (2 h). Highly porous and stable materials can be made without any post-synthetic activation. Here, the success of solvent-free synthesis of multi-module MOFs reflects the synergy between different modules, resulting in stable pore-partitioned materials, despite the fact that other competitive crystallization pathways with simpler framework compositions also exist.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Parametric and sensitivity analysis of a PCM-integrated wall for optimal thermal load modulation in lightweight buildings

Load modulation in buildings is becoming increasingly important due to growing disparity in energy demand during peak and off-peak hours. Integrating phase change material (PCM) in building envelopes and using a controlled precooling strategy can provide substantial thermal load modulation; however, it may greatly increase the total energy use. Previous studies have employed PCM in building envelopes primarily for energy savings and, to some extent, peak load shedding and shifting. However, the load modulation capacity of a PCM-integrated envelope has not been well explored in the literature. In this study, we perform an extensive parametric and sensitivity analysis on PCM-integrated lightweight building walls and examine the combinatory effects of various PCM parameters on thermal load modulation and wall-related heat gains in buildings. Using numerical simulations, we investigate eight PCM parameters: PCM location in the wall, transition temperature, thickness, latent heat, transition range, density, specific heat, and thermal conductivity. Here, we evaluate their impact and relative importance to achieve maximum load modulation in buildings without compromising occupants’ thermal comfort or total energy use. The results show that the optimized PCM proposed in this study can completely invert the transient heat gain profile of the wall, providing up to 70% reduction of wall-related heat gain during peak hours without a major increase in the cumulative heat gain.

42 ENGINEERING↗

Multi-module-based CVAE to predict HVCM faults in the SNS accelerator

We present a multi-module framework based on Conditional Variational Autoencoder (CVAE) to detect anomalies in the power signals coming from multiple High Voltage Converter Modulators (HVCMs). We condition the model with the specific modulator type to capture different representations of the $\mathcal{normal}$ waveforms and to improve the sensitivity of the model to identify a specific type of fault when we have limited samples for a given module type. We studied several Artificial Neural Network (ANN) architectures for our CVAE model and evaluated the model performance by looking at their loss landscape for stability and generalization. Our results for the Spallation Neutron Source (SNS) experimental data show that the trained model generalizes well to detecting multiple fault types for several HVCM module types. The results of this study can be used to improve the HVCM reliability and overall SNS uptime.

43 PARTICLE ACCELERATORS↗

Scalable semitransparent prototype organic photovoltaic module with minimal resistance loss

Semi-transparent organic photovoltaic (ST-OPV) cells are regarded as an attractive solution to building-integrated solar energy harvesting. Both the power conversion efficiency (PCE) and average photopic transmission (APT) of ST-OPVs have shown substantial increases in recent years. However, less attention has been paid to the area scaling of ST-OPV cells. In this work, we investigate the scalability of ST-OPV cells from 4 mm 2 to 1 cm 2 , as well as 9 cm 2 active area prototype module. By integrating both top and bottom metal grids onto the transparent electrodes, the series resistance loss of 1 cm 2 ST-OPV cell is significantly reduced, and is comparable to that of the grid-free 4 mm 2 cell. Nine 1 cm 2 cells are then connected in a series-parallel circuit to realize a prototype ST-OPV module. A 100% fabrication yield with only 5% PCE deviation among discrete cells is achieved. The semitransparent module shows PCE = 7.2 ± 0.1% under simulated AM 1.5G illumination at 1 sun intensity, which exhibits no connection resistance loss compared to that of the individual cells. The ST-OPV module exhibits an APT = 38.1 ± 1.1%, which enables a light utilization efficiency, LUE = 2.74 ± 0.09%. Here, the method demonstrates a promising way for ST-OPV modules to scale without compromising performance.

14 SOLAR ENERGY↗

Development of a plug-and-play anti-noise module for fault diagnosis of rotating machines in nuclear power plants

The health of rotating machines is crucial to the stable operation and safety of nuclear power plants. However, research on machine learning-based fault diagnosis of rotating machines in the nuclear industry is still in its infancy. The signal noise generated in the plant may negatively affect the effectiveness of the analysis. In this paper, a plug-and-play anti-noise machine learning module is proposed to fill the knowledge and capability gap. The modules are loaded into a convolutional neural network called deep residual network (ResNet) to obtain a new model with noise reduction capability. The basic idea is that the module is able to identify noise features and include them in the subsequent analysis, effectively filtering noise at the feature level of the network. Nine variants of the new model are compared with the original ResNet as well as four classical machine learning models to test the effectiveness of the module and to examine the impact of the module's loading modes on the performance of the new model. Finally, this research helps facilitate the application of machine learning in the plant noise environment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Computational design and analysis of modular cells for large libraries of exchangeable product synthesis modules

Microbial metabolism can be harnessed to produce a large library of useful chemicals from renewable resources such as plant biomass. However, it is laborious and expensive to create microbial biocatalysts to produce each new product. To tackle this challenge, we have recently developed modular cell (ModCell) design principles that enable rapid generation of production strains by assembling a modular (chassis) cell with exchangeable production modules to achieve overproduction of target molecules. Previous computational ModCell design methods are limited to analyze small libraries of around 20 products. In this study, we developed a new computational method, named ModCell-HPC, that can design modular cells for large libraries with hundreds of products with a highly-parallel and multi-objective evolutionary algorithm and enable us to elucidate modular design properties. We demonstrated ModCell-HPC to design Escherichia coli modular cells towards a library of 161 endogenous production modules. From these simulations, we identified E. coli modular cells with few genetic manipulations that can produce dozens of molecules in a growth-coupled manner with different types of fermentable sugars. These designs revealed key genetic manipulations at the chassis and module levels to accomplish versatile modular cells, involving not only in the removal of major by-products but also modification of branch points in the central metabolism. We further found that the effect of various sugar degradation on redox metabolism results in lower compatibility between a modular cell and production modules for growth on pentoses than hexoses. To better characterize the degree of compatibility, we developed a method to calculate the minimal set cover, identifying that only three modular cells are all needed to couple with up 85 compatible production modules. By determining the unknown compatibility contribution metric, we further elucidated the design features that allow an existing modular cell to be re-purposed towards production of new molecules. Altogether, ModCell-HPC is a useful tool for understanding modularity of biological systems and guiding more efficient and generalizable design of modular cells that help reduce research and development cost in biocatalysis.

59 BASIC BIOLOGICAL SCIENCES↗

Collisional simulations of the modulator section in coherent electron cooling

The first section of any coherent electron cooling (CeC) system is the modulator, where the density of the electron beam is modulated by the copropagating ion beam. This density modulation is a result of Coulomb collisions between the individual particles of the two beams. The pairwise, stochastic part of the interactions impacts the overall performance of the CeC process. We present the first simulations of the density modulations of the electron beams from a collisional picture of the dynamics, considering the proof-of-principle CeC experiments at Brookhaven National Laboratory. These simulations were performed using PHAD, which is the first efficient, large-scale collisional numerical method in beam physics that we have previously developed and benchmarked. Realistic beam distributions and external fields have been optimized to provide strong modulation signals necessary for variations of coherent electron cooling systems. Cooling performance limits and potential collisionless simulation pitfalls are pointed out. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

Rapid Prototyping Techniques for Organic Direct-Bonded-Copper Power Modules

Organic Direct-Bonded-Copper (ODBC) is a novel packaging technology for power modules which allows higher flexibility in layout design. In this work, a set of rapid prototyping techniques are developed for ODBC modules based on a polyimide dielectric material. These techniques enable fast and low-cost fabrication of modules with 3-Dimensional (3D) layout features. An example half-bridge (HB) silicon carbide (SiC) metal oxide semiconductor field effect transistor (MOSFET) module is designed and prototyped using the proposed techniques aiming at ultra-low power loop inductance. Finite element analysis (FEA)-circuit co-simulations results and experimental results validate an approximately 0.71nH power loop inductance for the example module design.

36 MATERIALS SCIENCE↗

Turn Your Half-Cut Cells for a Stronger Module

Here, we employ an existing model of crystalline silicon photovoltaic module cell fracture to explore the effect of cell size and orientation on their probability of fracture under module uniform loading. In addition, we also apply continuum damage mechanics to modify this model to consider the effect of cell fracture on the probability of subsequent cell fracture. We elucidate that cell fracture increases the probability of subsequent cell fracture and that rectangular modules containing half-cells aligned with the module's long orientation are much more robust against cell fracture than full-cell and half-cell short orientation modules.

14 SOLAR ENERGY↗

Sequential Stress Identifies Processing Defects in Bifacial Photovoltaic Modules That Limit Durability

Here, we use sequential stress to investigate hurdles to bifacial photovoltaic (PV) module durability from lamination defects. We test mini-modules with glass/glass (G/G) and glass/transparent-backsheet (G/TB) constructions using either ethylene vinyl acetate or polyolefin elastomer (POE) based encapsulants under a modified IEC 63209-2 sequential stress. This sequence includes multiple iterations of damp heat (DH200), full spectrum light exposure (A3), thermal cycling (TC50), and humidity/freeze (HF10). We compare indoor stress with outdoor exposure. Results show similar relative trends in degradation after a year outdoors compared to our first stress cycle. Subsequent stress cycles impart more severe damage than outdoor exposure for the short outdoor duration used here. Edge-pinch lamination defects in G/G mini-modules limit durability causing delamination and cell cracks. Conversely, we observe greater degradation in G/TB mini-modules compared to G/G in the later stages of the stress sequence when the backsheets are directly exposed to UV-containing light. Our results highlight: 1) the utility of sequential stress testing to uncover degradation modes in bifacial PV, 2) implications of using mini-modules for testing PV quality, and 3) the importance of lamination defects that must be avoided to ensure durability as the industry adopts G/G or G/TB packaging.

14 SOLAR ENERGY↗