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SynopFrame: Multiscale time-dependent visual abstraction framework for analyzing DNA nanotechnology simulations
We present an open-source framework, SynopFrame, that allows DNA nanotechnology (DNA-nano) experts to analyze and understand molecular dynamics simulation trajectories of their designs. We use a multiscale multi-dimensional abstraction space, connect the representations to a projected conformational space plot of the structure’s temporal sequence, and thus enable experts to analyze the dynamics of their structural designs and, specifically, failure cases of the assembly. In addition, our time-dependent abstraction representation allows the biologists, for the first time in a smooth and structurally clear way, to identify and observe temporal transitions of a DNA-nano design from one configuration to another, and to highlight important periods of the simulation for further analysis. We realize SynopFrame as a dashboard of the different synchronized 3D spatial and 2D schematic visual representations, with a color overlay to show essential properties such as the status of hydrogen bonds. The linking of the spatial, schematic, and abstract views ensures that users can effectively analyze the high-frequency motion. We also categorize the status of the hydrogen bonds into a new format to allow us to color-encode it and overlay it on the representations. To demonstrate the utility of SynopFrame, we describe example usage scenarios and report user feedback.
Synergistic data analytics for electromechanical oscillation in electric power systems
Accurate real-time estimation of the four electromechanical oscillation properties, i.e., dominant oscillation modes, mode shapes, participation factors, and coherent groups, is of great importance to assess and mitigate potential electromechanical oscillations in interconnected power systems. While eigenvalue analysis can realize such estimation, it requires precise linearized dynamic models and accurate parameters, which are highly difficult to obtain in practice. Data fusion-based modal estimation methods can extract the properties of electromechanical oscillations from measurement data without the power system model and parameters, but most of the time only one or two property assessments can be accomplished each time. To overcome this challenge, this paper presents a synergistic data analytics solution to characterize the dynamic behaviors of electromechanical oscillations from real-time measurement data. Here, the proposed method uses optimized variable projection, and it is capable of estimating all four electromechanical oscillation behavior properties from measured responses. Case studies are performed using the simulated measurement data of a 16-generator 68-bus test system and the field measurements collected by the PMUs deployed in the Yunnan Power Grid. The results demonstrate that the proposed synergistic data analytics solution can achieve satisfactory performance in capturing the properties of electromechanical oscillations from measurement data and exhibit strong robustness against measurement noise when compared with existing measurement-based methods.
Design and full core fuel performance assessment of high burnup cores for 4-loop PWRs
Increasing the fuel discharge burnup of current light water reactors (LWRs) promises reductions in fuel cycle and/or operations costs. By assuming a constant core power density, the economic gain is enabled by better fuel utilization and/or an increased capacity factor. In this effort to investigate greater than 62 MWd/kgU maximum rod average burnup for 110+ kW/l core power density, two core designs have been developed for a standard 17x17, 193 fuel assemblies pressurized water reactor (PWR). The levelized unit cost methodology is employed to evaluate fuel cycle, operation and maintenance, and capital cost impacts and to examine the economic viability of both core design pathways. Core design and optimization are performed using the commercial STUDSVIK code package. Fuel performance analysis is realized in full core configuration via auditing FRAPCON4.1, FAST1.2, and the high-fidelity code BISON. To provide a realistic assessment, the core design process takes into consideration best practices in current PWR core design. It features acceptable performance in terms of various core design constraints on maximum allowable peaking and boron concentration. Gadolinia (Gd2O3) is used as a burnable poison with a maximum of 9 wt% concentration while feeding 89 or 77 fuel assemblies in a 3-batch refueling scheme. Full core fuel performance simulation, which allows for characterization of relevant fuel temperatures, plenum pressures, stresses, and strains, is performed with respect to two bounding burnup levels. Such performance is potentially licensable for the 18-month high burnup core (<68 MWd/kgU peak pin), while it is more challenging for the 24-month high burnup core design pathway (<75 MWd/kgU peak pin). Maximum rod plenum pressure is identified as the most limiting fuel performance parameter. Here, while the scope of the present study focuses on the steady-state plus overpower conditions, the acceptability of the new discharge burnup has to be further assessed by considering uncertainties and impacts under accident scenarios in the future.
Mitigation of safety and environmental challenges posed by refrigerants
The abatement of safety and environmental burden associated with low and ultra-low Global Warming Potential (GWP) refrigerants is a critical undertaking. As the industry shifts towards more environmentally friendly alternatives, mitigating the potential risks and ensuring safety standards becomes paramount. The adoption of mildly and highly flammable refrigerants contributes significantly to minimizing the greenhouse gas impact on the environment, aligning with global climate and sustainability goals. However, it is essential to address safety concerns and potential environmental implications associated with the end use of these refrigerants. A method to mitigate the safety risk in a flammable refrigerant based heating, ventilation, air-conditioning, and refrigeration (HVACR) system is the primary focus of this paper. Advent of A2L and A3 refrigerants as replacements to high GWP refrigerants requires careful handling of leak episodes to lower or eliminate the risk associated with creating flammable mixtures capable of fire/explosion hazard. Solid materials tailored to target the molecule of interest (i.e., refrigerant.) by engineering the microporous structure as well as chemically functionalizing the surface to attract and hold on to the chemical compound being removed from the gas stream was realized. Quantitative analysis reveals the adsorbent's effectiveness in reducing leak potential in the range of 40 %–100 % for various refrigerants. Strategic placement and active leak management with negative pressure offer promising avenues for capturing leaked refrigerants, enhancing overall safety.
Optimization and Techno-Economic Comparison of Regenerators and Recuperators in sCO2 Recompression Brayton Cycles for Concentrating Solar Power Applications
Supercritical CO2 power cycles might be capable of providing the cost reductions and efficiency improvements necessary to reach concentrating solar power (CSP) cost targets, but require large, highly effective recuperators. Fixed-bed regenerators are a periodic heat exchanger that could be an effective yet low-cost alternative to these recuperators. This study presents a techno-economic comparison of regenerators and recuperators for a 100 MWe supercritical CO2 power cycle for CSP applications. We quantify the levelized cost of energy (LCOE) for the power plant with both types of heat exchangers, and explore sensitivity of LCOE to parameters such as CSP-specific capital costs, power cycle component capital costs, and regenerator valve replacements costs. Results indicate that the incumbent printed circuit heat exchangers achieve the lowest LCOE, unless the upper extreme of PCHE capital cost and lower extremes of regenerator and valve capital and O&M costs are realized. Sensitivity analysis also illustrates that the primary heat exchanger cost is the most influential of power cycle components, and that CSP component capital cost is more influential than power cycle capital costs. This illustrates the importance of reducing the cost of heliostats, receivers, and thermal energy storage for achieving CSP LCOE targets.
Periodic Trends from Metal Substitution in Bimetallic Mo-Based Phosphides for Hydrodeoxygenation and Hydrogenation Reactions
Bimetallic phosphides are promising materials for biomass valorization, yet many metal combinations are understudied as catalysts and require further analysis to realize their superior properties. Herein, we provide the synthesis, characterization, and catalytic performance of a variety of period 4 and 5 solid solutions of molybdenum-based bimetallic phosphides (MMoP, M = Fe, Co, Ni, Ru). From the results, the charge sharing between the metals and phosphorus control the relative oxidation of Mo and reduction of P in the lattice, which were both indirectly observed in binding energy shifts in X-ray photoelectron spectroscopy (XPS) and absorption energy shifts in X-ray absorption near-edge spectroscopy (XANES). For MMoP (M = Fe, Co, Ni), the more oxidized the Mo in the bimetallic phosphide, the higher the selectivity to benzene from phenol via direct deoxygenation at 400 °C and 750 psig. This phenomenon was observed in the bimetallic materials synthesized across period 4, where aromatic selectivity and degree of Mo oxidation both decreased in the following order FeMoP >> CoMoP > NiMoP. Alternatively, in the case of MMoP (M = Fe, Ru), the P in RuMoP is more oxidized compared to that in FeMoP, and the selectivity toward the hydrogenation pathway increased due to the interaction between the aromatic rings and the P species on the surface. For RuMoP and NiMoP, cyclohexanol was selectively produced from phenol with >99% selectivity when the reaction temperature was lowered to 125 °C at 750 psig, whereas FeMoP and CoMoP were not active under these conditions. Last, complete deoxygenation of phenol to benzene, cyclohexane, and cyclohexene was accomplished using mixtures of RuMoP and FeMoP in flow and batch experiments. Furthermore, these results highlight the versatility and wide applicability of transition metal phosphides for biomass conversions.
Adoption of Light-Emitting Diodes in Common Lighting Applications
The 2020 edition of a report which models the current state of the U.S. general-lighting market and provides analysis on realized and potential energy- and money-saving benefits associated with LED lamps and luminaires.
Development of a process for producing ribbon shaped filaments
Silicon carbide (SiC) ribbon filaments were produced on a carbon ribbon substrate, about 1500 microns (60 mils) wide and 100 microns (4 mils) thick in lengths up to 2 meters (6 ft), and with tensile strengths up to 142 KN/cm sq (206 Ksi). During the course of the study, ribbon filaments of boron were also produced on the carbon ribbon substrate; the boron ribbon produced was extremely fragile. The tensile strength of the SiC ribbon was limited by large growths or flaws caused by anomalies at the substrate surface; these anomalies were either foreign dirt or substrate imperfections or both. Related work carried out on round 100 micron (4 mils) diameter SiC filaments on a 33 micron (1.3 mil) diameter, very smooth carbon monofilament substrate has shown that tensile strengths as high as 551 KN/cm sq (800 Ksi) are obtainable with the SiC-carbon round substrate combination, and indicates that if the ribbon substrate surface and ribbon deposition process can be improved similar strengths can be realizable. Cost analysis shows that 100 micron x 5-10 micron SiC ribbon can be very low cost reinforcement material.
Insight and Evidence Motivating the Simplification of Dual-Analysis Hybrid Systems into Single-Analysis Hybrid Systems
Many hybrid data assimilation systems currently used for NWP employ some form of dual-analysis system approach. Typically a hybrid variational analysis is responsible for creating initial conditions for high-resolution forecasts, and an ensemble analysis system is responsible for creating sample perturbations used to form the flow-dependent part of the background error covariance required in the hybrid analysis component. In many of these, the two analysis components employ different methodologies, e.g., variational and ensemble Kalman filter. In such cases, it is not uncommon to have observations treated rather differently between the two analyses components; recentering of the ensemble analysis around the hybrid analysis is used to compensated for such differences. Furthermore, in many cases, the hybrid variational high-resolution system implements some type of four-dimensional approach, whereas the underlying ensemble system relies on a three-dimensional approach, which again introduces discrepancies in the overall system. Connected to these is the expectation that one can reliably estimate observation impact on forecasts issued from hybrid analyses by using an ensemble approach based on the underlying ensemble strategy of dual-analysis systems. Just the realization that the ensemble analysis makes substantially different use of observations as compared to their hybrid counterpart should serve as enough evidence of the implausibility of such expectation. This presentation assembles numerous anecdotal evidence to illustrate the fact that hybrid dual-analysis systems must, at the very minimum, strive for consistent use of the observations in both analysis sub-components. Simpler than that, this work suggests that hybrid systems can reliably be constructed without the need to employ a dual-analysis approach. In practice, the idea of relying on a single analysis system is appealing from a cost-maintenance perspective. More generally, single-analysis systems avoid contradictions such as having to choose one sub-component to generate performance diagnostics to another, possibly not fully consistent, component.
Mars 2020 Thermal Protection Systems Sizing and Development
The Mars 2020 spacecraft delivering the Perseverance Rover to Mars was planned to be a build-to-print repeat of the Mars Science Laboratory (MSL) spacecraft that delivered the Curiosity Rover to Mars in 2012. The 2020 mission would deliver a slightly higher mass at a lower entry velocity, so the mission designers were comfortable with the cost saving approach of using an already proven design. The approach used in sizing the thermal protection systems (TPS) for the various components of the MSL spacecraft included convective heating and shock layer radiation (a small contributor) on the heatshield and only convective heating on all of the aft body parts. At the time, it was assumed that the contribution of radiation from the shock layer and the wake was negligible on the aft body at Mars. In the time since the MSL spacecraft was designed, in light of new data and analysis, NASA realized the significance of radiative heating in the aftbody on vehicles entering Mars, beginning with the InSight entry. New analyses showed that the radiant heat fluxes on aft body components at Mars were of the same order or even larger than predicted convective heat fluxes. The Mars 2020 team was tasked with showing that the TPS thicknesses designed for MSL with only convective heating would survive the Mars 2020 convective plus radiative heat flux environments. Luckily, many of the MSL aft body components were sized using an extra conservative approach, often sizing for the worst environment at the lightest, thinnest structure, even though the environments and structures were not co-located. The Mars 2020 team had to more accurately evaluate the environments and structures to show that the design would close
NWGraph: A Library of Generic Graph Algorithms and Data Structures in C++20
The C++ Standard Library is a valuable collection of generic algorithms and data structures that improves the usability and reliability of C++ software. Graph algorithms and data structures are notably absent from the standard library, and previous attempts to fill this gap have not gained widespread adoption. In this paper we show that the richness of graph algorithms and data structures can in fact be captured by straightforward composition of existing C++ mechanisms. Generic programming is algorithm-oriented. Accordingly, we apply a systematic approach to analyzing a broad set of graph algorithms, “lift” unnecessary constraints from them, and organize the resulting set of minimal common type requirements, i.e., concepts, for defining their interfaces. By using the newly available ranges and concepts in C++20, the type requirements for generic graph algorithms can be succinctly expressed. The generic algorithms and data structures resulting from our analysis are realized in NWGraph, in a modern, composable, and extensible C++ library.
Workshop Report: 2021 International Symposium of Quantitative Codesign of Supercomputers
This report provides general information about the First International Symposium on the Quantitative Design of Supercomputers (SQCS). This new workshop was held in conjunction with Supercomputing ’21 on November 19, 2021, in St Louis Missouri. The symposium aims at combining two methodologies—collaborative codesign and data-driven analysis—to realize the potential of supercomputing more fully. We refer to the design solutions that rely on intelligence from data-driven insights across applications, systems, system software, workflows, and facilities as quantitative codesign of supercomputers.
Workshop Report: 2022 International Symposium of Quantitative Codesign of Supercomputers
This report provides general information about the Second International Symposium on the Quantitative Design of Supercomputers (SQCS). This new workshop was held in conjunction with Supercomputing ’22 on November 13, 2022, in Dallas Texas. The symposium aims at combining two methodologies—collaborative codesign and data-driven analysis—to realize the potential of supercomputing more fully. We refer to the design solutions that rely on intelligence from data-driven insights across applications, systems, system software, workflows, and facilities as quantitative codesign of supercomputers.
Realizability Checking of Requirements in FRET
Requirements formalization has become increasingly popular in industrial settings as an effort to disambiguate designs and optimize development time and costs for critical system components. Formal requirements elicitation also enables the employment of analysis tools to prove important properties, such as consistency and realizability. In this report, we present the realizability analysis framework that we developed as part of the Formal Requirements Elicitation Tool (FRET). Our framework prioritizes usability, and employs state-of-the-art analysis algorithms that support infinite theories. We demonstrate the workflow for realizability checking, showcase the diagnosis process that supports visualization of conflicts between requirements and simulation of counterexamples, and discuss results from industrial-level case studies.
Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado
Abstract. Deep learning (DL)-assisted inverse mapping has shown promise in hydrological model calibration by directly estimating parameters from observations. However, the increasing computational demand for running the state-of-the-art hydrological model limits sufficient ensemble runs for its calibration. In this work, we present a novel knowledge-informed deep learning method that can efficiently conduct the calibration using a few hundred realizations. The method involves two steps. First, we determine decisive model parameters from a complete parameter set based on the mutual information (MI) between model responses and each parameter computed by a limited number of realizations (∼50). Second, we perform more ensemble runs (e.g., several hundred) to generate the training sets for the inverse mapping, which selects informative model responses for estimating each parameter using MI-based parameter sensitivity. We applied this new DL-based method to calibrate a process-based integrated hydrological model, the Advanced Terrestrial Simulator (ATS), at Coal Creek Watershed, CO. The calibration is performed against observed stream discharge (Q) and remotely sensed evapotranspiration (ET) from the water year 2017 to 2019. Preliminary MI analysis on 50 realizations resulted in a down-selection of 7 out of 14 ATS model parameters. Then, we performed a complete MI analysis on 396 realizations and constructed the inverse mapping from informative responses to each of the selected parameters using a deep neural network. Compared with calibration using observations covering all time steps, the new inverse mapping improves parameter estimations, thus enhancing the performance of ATS forward model runs. The Nash–Sutcliffe efficiency (NSE) of streamflow predictions increases from 0.53 to 0.8 when calibrating against Q alone. Using ET observations, on the other hand, does not show much improvement on the performance of ATS modeling mainly due to both the uncertainty of the remotely sensed product and the insufficient coverage of the model ET ensemble in capturing the observation. By using observed Q only, we further performed a multiyear analysis and show that Q is best simulated (NSE > 0.8) by including in the calibration the dry-year flow dynamics that show more sensitivity to subsurface characteristics than the other wet years. Moreover, when continuing the forward runs till the end of 2021, the calibrated models show similar simulation performances during this evaluation period as the calibration period, demonstrating the ability of the estimated parameters in capturing climate sensitivity. Our success highlights the importance of leveraging data-driven knowledge in DL-assisted hydrological model calibration.
Probability of Pinching Failure in PWR SNF after Long-Term Storage
A probabilistic assessment was performed on pinching failure of PWR SNF rod cladding under accidental SNF cask transport conditions. a set of 3,000 rod pinching scenarios was analyzed, with different geometrical, material, and loading parameters, using a Latin Hypercube Sampling (LHS). The investigated accidents include train derailments leading to cask collisions or cask drops. Pinching failure was related to cladding offset strain, defined as the plastic deformation interval in radial cladding direction normalized with respect to the outer cladding diameter. Finite element (FE) models were used to compute SNF rod deformations and the offset strain demand OSD in each of the assessed pinching scenarios. The numerical models account for the contribution of the degraded fuel pellets to rod pinching stiffness. The offset strain capacity OSC was computed using regression and interpolation models based on ring compression (RCT) test results, and account for hydride-related effects on cladding ductility. The results show a low probability of pinching failure. Hydride-related cladding embrittlement affects the structural integrity of PWR SNF rods after long-term dry storage of up to 300 years. Radial hydride patterns or large amounts of circumferentially oriented hydrides reduce the cladding ductile deformation capability when pinched at low material temperatures. The probability of hydride-related pinching failure of PWR cladding is estimated after long-term dry storage to address: How do PWR SNF rod conditions like hydrogen content, vacuum drying peak cladding hoop stress σ{sub θ}, and cladding material temperature affect cladding ductility? Is hydride-related cladding embrittlement a material degradation mechanism that affects the structural integrity of PWR SNF rods under pinching loading? What are the controlling parameters for deformation demands in PWR SNF rods under pinching loading? Is the pinching load amplitude an important parameter that controls the probability of pinching failure? How do parameters like pellet-cladding gap or fuel pellet degradation affect the pinching loading capacity of PWR SNF rods? Statistical modelling of PWR SNF rod conditions in U.S. inventory: A pseudo rod database was generated based on EIA database. Analysis of train accident scenarios: a probability density function (pdf) of a pinching load distribution P{sub 9m} of a 9-m cask drop is linearly scaled to generate a more representative: distribution P{sub AS}. The new distribution considers train collision velocities, cask drops for on- and off-bridge accidents, and cask impact orientation. LHS generates 3,000 rod pinching scenarios based on nine independent geometrical, material, and loading parameters. Probabilistic FE Analysis: The LHS realizations are used to generate 3,000 FE models. The FE analysis is conducted for P{sub 9m}, and P{sub AS}. The workflow is automatized. The OSC is computed with regression and interpolation models, as a function of the hydrogen content C{sub H}, vacuum drying peak σ{sub θ}, and SNF temperature T{sub FR}: The regression data was obtained in RCTs on PWR cladding. The OSD is derived from the cladding deformations in the FE models. Cladding failure was identified via a comparison of OSC and OSD. A 300 and a 30 years-of-dry-storage duration is investigated: The dry-storage period affects the expected SNF temperature and consequently, the OSC and the OSD. The material temperature LHS population is adapted to account for a SNF temperature variation. The probability of hydride-related, ductile cladding failure during a severe transportation accident is not significantly affected by the pinching load amplitude: The probability is slightly reduced from a range of less than 0.0333% to 0.1667% for P{sub 9m}, to a range of less than 0.0333% to 0.1333% for P{sub AS}, depending on the vacuum drying peak cladding hoop stress modelling assumptions. Further, the SNF dry-storage duration does not significantly affect the probability of ductile pinching failure. Based on available train accidents data, the pinching failure probability for a 5,000 km long transportation route ranges from less than 1.62 E-7 to a value of 6.47 E-7, depending on the vacuum drying peak cladding hoop stress modelling assumptions. The pinching load amplitude is not a controlling parameter for the probability of ductile cladding pinching failure, and does not control the cladding deformations once pellet-cladding contact is established, The pellet-cladding gap width, however, plays a key role. Fuel pellet degradation only affects the deformation capacity, if the pellet stiffness is significantly reduced (more than 90%). Only highly embrittled cladding is likely to fail. The deformation demands on the cladding under pinching loading are small.
Uncertainty propagation through an aeroelastic wind turbine model using polynomial surrogates
Polynomial surrogates are used to characterize the energy production and lifetime equivalent fatigue loads for different components of the DTU 10 MW reference wind turbine under realistic atmospheric conditions. The variability caused by different turbulent inflow fields are captured by creating independent surrogates for the mean and standard deviation of each output with respect to the inflow realizations. A global sensitivity analysis shows that the turbulent inflow realization has a bigger impact on the total distribution of equivalent fatigue loads than the shear coefficient or yaw miss-alignment. The methodology presented extends the deterministic power and thrust coefficient curves to uncertainty models and adds new variables like damage equivalent fatigue loads in different components of the turbine. These surrogate models can then be implemented inside other work-flows such as: estimation of the uncertainty in annual energy production due to wind resource variability and/or robust wind power plant layout optimization. It can be concluded that it is possible to capture the global behavior of a modern wind turbine and its uncertainty under realistic inflow conditions using polynomial response surfaces. In conclusion, the surrogates are a way to obtain power and load estimation under site specific characteristics without sharing the proprietary aeroelastic design.