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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Chemical transformations and transport phenomena at interfaces

Abstract Interfaces, the boundary that separates two or more chemical compositions and/or phases of matter, alters basic chemical and physical properties including the thermodynamics of selectivity, transition states, and pathways of chemical reactions, nucleation events and phase growth, and kinetic barriers and mechanisms for mass transport and heat transport. While progress has been made in advancing more interface‐sensitive experimental approaches, their interpretation requires new theoretical methods and models that in turn can further elaborate on the microscopic physics that make interfacial chemistry so unique compared to the bulk phase. In this review, we describe some of the most recent theoretical efforts in modeling interfaces, and what has been learned about the transport and chemical transformations that occur at the air–liquid and solid–liquid interfaces. This article is categorized under: Structure and Mechanism > Reaction Mechanisms and Catalysis Structure and Mechanism > Computational Materials Science Software > Quantum Chemistry Software > Simulation Methods

Hao, Hongxia↗
DOE OSTI2022

Parked aeroelastic field rotor response for a 20% scaled demonstrator of a 13‐MW downwind turbine

Abstract Aeroelastic parked testing of a unique downwind two‐bladed subscale rotor was completed to characterize the response of an extreme‐scale 13‐MW turbine in high‐wind parked conditions. A 20% geometric scaling was used resulting in scaled 20‐m‐long blades, whose structural and stiffness properties were designed using aeroelastic scaling to replicate the nondimensional structural aeroelastic deflections and dynamics that would occur for a lightweight, downwind 13‐MW rotor. The subscale rotor was mounted and field tested on the two‐bladed Controls Advanced Research Turbine (CART2) at the National Renewable Energy Laboratory's Flatiron Campus (NREL FC). The parked testing of these highly flexible blades included both pitch‐to‐run and pitch‐to‐feather configurations with the blades in the horizontal braked orientation. The collected experimental data includes the unsteady flapwise root bending moments and tip deflections as a function of inflow wind conditions. The bending moments are based on strain gauges located in the root section, whereas the tip deflections are captured by a video camera on the hub of the turbine pointed toward the tip of the blade. The experimental results are compared against computational predictions generated by FAST, a wind turbine simulation software, for the subscale and full‐scale models with consistent unsteady wind fields. FAST reasonably predicted the bending moments and deflections of the experimental data in terms of both the mean and standard deviations. These results demonstrate the efficacy of the first such aeroelastically scaled turbine test and demonstrate that a highly flexible lightweight downwind coned rotor can be designed to withstand extreme loads in parked conditions.

17 WIND ENERGY↗
DOE OSTI2018

An introduction to partial differential equations constrained optimization

Partial differential equation (PDE) constrained optimization is designed to solve control, design, and inverse problems with underlying physics. A distinguishing challenge of this technique is the handling of large numbers of optimization variables in combination with the complexities of discretized PDEs. Over the last several decades, advances in algorithms, numerical simulation, software design, and computer architectures have allowed for the maturation of PDE constrained optimization (PDECO) technologies with subsequent solutions to complicated control, design, and inverse problems. This special journal edition, entitled “PDE-Constrained Optimization”, features eight papers that demonstrate new formulations, solution strategies, and innovative algorithms for a range of applications. In particular, these contributions demonstrate the impactfulness on our engineering and science communities. This paper offers short remarks to provide some perspective and background for PDECO, in addition to summaries of the eight papers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Energy efficient photonic millimeter-wave generation using cascaded polarization modulators

A filter-less millimeter-wave generation scheme consisting of four polarization modulators in series, each followed by a polarizer is proposed to achieve optoelectronic frequency octupling. The cascade of polarization modulator and polarizer provides an intensity modulator whose biasing condition can be set by the polarizer angle and polarization state of the input light to each polarization modulator. A theoretical analysis of the architecture is performed using a transfer function method and validated by industry-standard software simulation tools. The circuit shows high potential in achieving desired performance with lower input RF power when compared to the another configuration based on a generalized Mach–Zehnder interferometer structure. Although the operating range in terms of applied RF drive becomes narrow, low RF input operation can be achieved by this circuit. The effect of imbalances in the key circuit parameters is also investigated in terms of electrical side harmonic suppression ratio.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Computation of Effective Radiative Properties of Powders for Selective Laser Sintering Simulations

Selective laser sintering (SLS) is an additive manufacturing technique for rapidly creating parts directly from a computer-aided design (CAD) model by using a laser to fuse successive layers of powder. However, better understanding of the effect of particle-level variations on the overall build quality is needed. In this work, we investigated these effects computationally by considering the role of the particle size distribution and variations in the powder bed depth to mimic the part complexity found in overhangs and protrusions. In addition, the results from these studies can be distilled to obtain better effective material properties such as laser absorptivity and laser extinction coefficient that are needed for continuum models of the process. We implement a Monte Carlo ray-tracing algorithm within the discrete element model in the open-source simulation software MFiX. Random, loose-packed, particle bed structures are generated, and effective absorptivity and extinction coefficients are calculated. Results are compared against previous computational and experimental measurements for free, monodisperse, and deep powder beds, with good agreement being obtained. Correlations along with uncertainties are developed to allow the effective absorptivity and extinction coefficient as a function of various particle and operational parameters to be accurately set in SLS macroscale models.

Moser, Daniel↗
DOE OSTI2017

Energy savings potential from improved building controls for the US commercial building sector

The U.S. Department of Energy’s (DOE’s) Building Technologies Office (BTO) sponsored a study to determine the potential national savings achievable in the commercial building sector through widespread deployment of best practice controls, elimination of system and component faults, and use of better sensing. Detailed characterization of potential savings was one source of input to set research, development, and deployment (RD&D) goals in the field of building sensors and controls. DOE’s building energy simulation software, EnergyPlus, was employed to estimate the potential savings from 34 measures in 9 building types and across 16 climates representing almost 57% of commercial building sector energy consumption. In addition to estimating savings from individual measures, three packages of measures were created to estimate savings from the packages. These packages represented an 1) efficient building, 2) typical building, and 3) inefficient building. To scale the results from individual measures or a package to the national scale, building weights by building type and climate locations from the Energy Information Administration’s 2012 Commercial Building Energy Consumption Survey (CBECS) were used. The results showed significant potential for energy savings across all building types and climates. The total site potential savings from individual measures by building type and climate location ranged between 0% and 25%. The total site potential savings by building type aggregated across all climates (using the CBECS building weights) for each measure varied between 0% and 16%. The total site potential savings aggregated across all building types and climates for each measure varied between 0% and 11%. Some individual measures had negative savings because correcting underlying operational problems (e.g., inadequate ventilation) resulted in increased energy consumption. When combined into packages, the overall national savings potential is estimated to be 29%; seven of the nine building types were in the range of 23 to 29% and two exceeded 40%. The total potential national site savings in for each building type ranged between 95x106 GJ (0.09 Quadrillion British thermal units [Quads]; Large Hotels) to 222x106 GJ (0.21 Quads; Large Office, Hospital Administrative areas, and College/University), resulting in total site savings of 1,393x106 GJ (1.32 Quads) when the three packages are applied to the U.S. commercial buildings stock. Using the source (or primary) energy conversion factors of 1.05 for natural gas and 3.14 for electricity resulted in an approximate potential primary energy savings of 2,912x106 GJ (2.76 Quads), which would be 15% of the sector’s 2015 use of approximately 18,991x106 GJ (18 Quads). Extrapolating the results for other building types not analyzed as part of this study, the primary energy savings could be in the range of 4,220x106 GJ to 5,275x106 GJ (4 to 5 Quads). If this savings potential is realized, it would be equivalent to not combusting 180 to 230 million tons of coal or reducing the energy impacts, at today’s energy intensities, of the per capita consumption of 12 to 15 million people in the U.S. To realize most of this potential savings, many gaps can be addressed through RD&D, as recommended in this paper.

Fernandez, Nick↗
DOE OSTI2022

Sensitivity analysis of generic deep geologic repository with focus on spatial heterogeneity induced by stochastic fracture network generation

Geologic Disposal Safety Assessment Framework is a state-of-the-art simulation software toolkit for probabilistic post-closure performance assessment of systems for deep geologic disposal of nuclear waste developed by the United States Department of Energy. This paper presents a generic reference case and shows how it is being used to develop and demonstrate performance assessment methods within the Geologic Disposal Safety Assessment Framework that mitigate some of the challenges posed by high uncertainty and limited computational resources. Variance-based global sensitivity analysis is applied to assess the effects of spatial heterogeneity using graph-based summary measures for scalar and time-varying quantities of interest. Behavior of the system with respect to spatial heterogeneity is further investigated using ratios of water fluxes. This analysis shows that spatial heterogeneity is a dominant uncertainty in predictions of repository performance which can be identified in global sensitivity analysis using proxy variables derived from graph descriptions of discrete fracture networks. New quantities of interest defined using water fluxes proved useful for better understanding overall system behavior.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Stochastic scheduling for commercial building cooling systems: considering uncertainty in zone temperature prediction

Here, this paper presents the first attempt to address the uncertainty in zone temperature prediction with stochastic optimization. The uncertain zone temperature is a process uncertainty and has not been considered in the existing stochastic optimization for building control. To fill this gap, we proposed a novel formulation of stochastic optimization to handle process uncertainty in building control. Specifically, we first examined the accuracy of a typical linear model for predicting zone temperature. We then formulated the scheduling of the building cooling system as a stochastic optimization problem over a 24-hour look-ahead period to minimize the electricity cost of the studied building cooling system. After that, we applied the proposed stochastic load scheduling (SLS) to a direct expansion (DX) cooling system that serves a medium office building. Through simulation with a detailed building energy simulation software, EnergyPlus, we evaluated the operational cost and the thermal comfort compared with a deterministic load scheduling. The operation cost of scheduling was found to vary with the level of zone temperature prediction uncertainty. The proposed SLS can mitigate the impacts of uncertain zone temperature predictions on both operational cost and thermal comfort. The evaluation results indicate that the proposed SLS works better when the uncertainty level is more significant.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Effect of occupant behavior on peak cooling and dehumidification loads in typical and high-efficiency homes

Residential building codes and voluntary labeling programs are continually increasing the energy efficiency requirements of residential buildings. Improving a building's thermal enclosure, installing the ductwork in conditioned space, and improving the building's airtightness results in significant reductions in externally-driven sensible and latent cooling loads. As a building's efficiency is improved, occupant-related internal gains become a larger portion of the building sensible and latent loads. Additionally, internal gains are highly uncertain compared to other load components. In this study, we use a stochastic approach to simulate occupant-related internal gains and compare the internal gains to other sensible and latent heat sources in four house efficiency levels in 10 U.S. climates using whole-building energy simulation software. We compare the expected range in occupant-related internal gains to other building characteristics such as cooling set point, air infiltration rate, and mechanical ventilation rate. We show that in high-efficiency homes, sensible internal gains vary from less than 10% to greater than 40% of the building sensible load under peak total cooling conditions depending on climate and internal gain profile. Likewise, latent internal gains vary from less than 10% to more than 60% of the building latent load under peak total cooling and peak dehumidification conditions depending on climate and internal gain profile.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Impact of heating and cooling loads on battery energy storage system sizing in extreme cold climates

Efficient operation of battery energy storage systems requires that battery temperature remains within a specific range. Current techno-economic models neglect the parasitic loads heating and cooling operations have on these devices, assuming they operate at constant temperature. In this work, these effects are investigated considering the optimal sizing of battery energy storage systems when deployed in cold environments. Here, a peak shaving application is presented as a linear programming problem which is then formulated in the PYOMO optimization programming language. The building energy simulation software EnergyPlus is used to model the heating, ventilation, and air conditioning load of the battery energy storage system enclosure. Case studies are conducted for eight locations in the United States considering a nickel manganese cobalt oxide lithium ion battery type and whether the power conversion system is inside or outside the enclosure. The results show an increase of 42% to 300% in energy capacity size, 43% to 217% in power rating, and 43% to 296% increase in capital cost dependent on location. This analysis shows that the heating, ventilation, and air conditioning load can have a large impact on the optimal sizes and cost of a battery energy storage system and merit consideration in techno-economic studies.

25 ENERGY STORAGE↗
DOE OSTI2015

Sparing Healthy Tissue and Increasing Tumor Dose Using Bayesian Modeling of Geometric Uncertainties for Planning Target Volume Personalization

Objective: To develop a mathematical tool that can update a patient's planning target volume (PTV) partway through a course of radiation therapy to more precisely target the tumor for the remainder of treatment and reduce dose to surrounding healthy tissue. Methods and Materials: Daily on-board imaging was used to collect large datasets of displacements for patients undergoing external beam radiation therapy for solid tumors. Bayesian statistical modeling of these geometric uncertainties was used to optimally trade off between displacement data collected from previously treated patients and the progressively accumulating data from a patient currently partway through treatment, to optimally predict future displacements for that patient. These predictions were used to update the PTV position and margin width for the remainder of treatment, such that the clinical target volume (CTV) was more precisely targeted. Results: Software simulation of dose to CTV and normal tissue for 2 real prostate displacement datasets consisting of 146 and 290 patients treated with a minimum of 30 fractions each showed that re-evaluating the PTV position and margin width after 8 treatment fractions reduced healthy tissue dose by 19% and 17%, respectively, while maintaining CTV dose. Conclusion: Incorporating patient-specific displacement patterns from early in a course of treatment allows PTV adaptation for the remainder of treatment. This substantially reduces the dose to healthy tissues and thus can reduce radiation therapy–induced toxicities, improving patient outcomes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Continuous condensed-phase ethanol conversion to higher alcohols: Experimental results and techno-economic analysis

The conversion of ethanol to n-butanol and higher alcohols is carried out in a continuous fixed bed reactor over a Ni/La 2 O 3 /γ-Al 2 O 3 catalyst at 210–250 °C and 100 bar. At these conditions, the reaction mixture is a condensed, near-critical phase that facilitates higher reaction rates than corresponding vapor phase reactions. Combined selectivity to n-butanol and C 6 + higher alcohols reached 74% at 41% ethanol conversion. A process concept is presented in which n-butanol and mixed C 6 + alcohols are produced as saleable products; ethanol is recycled to achieve nearly 100% overall conversion and minor byproducts are burned to provide process energy. A process design is conducted using Aspen Plus V8.4 process simulation software, and economic analyses are carried out for several cases of ethanol conversion and alcohol selectivities. Several additional cases involving permutations of the base process configuration are also examined in attempts to improve process economics. At n-butanol selectivities achieved experimentally, a facility producing 75 million kg n-butanol per year has a total capital cost of 38.1 million with a required n-butanol selling price of 1.55/kg to 1.60/kg for typical values of expected return on investment.

09 BIOMASS FUELS↗
DOE OSTI2022

Scan strategies in EBM-printed IN718 and the physics of bulk 3D microstructure development

Three-dimensional (3D) characterization provides opportunities for understanding processing-structure relationships in additively manufactured (AM) materials. Bulk samples of Inconel 718 were fabricated via electron beam melting (EBM) in order to study microstructural development as a function of energy input and beam scan strategy. TriBeam tomography of bulk Inconel 718 microstructures built under steady-state growth conditions reveals the sensitivity of microstructure formation and evolution to machine process parameters. Here, samples manufactured using a narrow range of energy input per unit build area result in varied grain morphologies and crystallographic textures. Using TRUCHAS, a thermal simulation software, the thermal history of bulk scan strategies was predicted, and combined with a calibrated microstructure-processing map to accurately predict bulk grain morphologies. The solidification parameters and the 3D measured nucleation density are used to predict the transition between columnar and equiaxed grain morphologies, providing a process map to guide AM parameter choices to locally control as-printed microstructure. A two-dimensional metric for characterizing bulk grain morphology was also found to agree well with predictions from the process map calibrated by 3D data. Combined with 3D tomography and thermal modelling, the physics of structure development were understood at a new level of detail with respect to the competing processes of grain nucleation and epitaxial growth.

36 MATERIALS SCIENCE↗
DOE OSTI2017

A gating grid driver for time projection chambers

A simple but novel driver system has been developed to operate the wire gating grid of a Time Projection Chamber (TPC). This system connects the wires of the gating grid to its driver via low impedance transmission lines. When the gating grid is open, all wires have the same voltage allowing drift electrons, produced by the ionization of the detector gas molecules, to pass through to the anode wires. When the grid is closed, the wires have alternating higher and lower voltages causing the drift electrons to terminate at the more positive wires. Rapid opening of the gating grid with low pickup noise is achieved by quickly shorting the positive and negative wires to attain the average bias potential with N-type and P-type MOSFET switches. The circuit analysis and simulation software SPICE shows that the driver restores the gating grid voltage to 90% of the opening voltage in less than 0.20 µs, for small values of the termination resistors. When tested in the experimental environment of a time projection chamber larger termination resistors were chosen so that the driver opens the gating grid in 0.35 µs. In each case, opening time is basically characterized by the RC constant given by the resistance of the switches and terminating resistors and the capacitance of the gating grid and its transmission line. By adding a second pair of N-type and P-type MOSFET switches, the gating grid is closed by restoring 99% of the original charges to the wires within 3 µs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Mitigation of shunt in poly -Si/SiO$_{x}$ passivated interdigitated back contact monocrystalline Si solar cells by self-aligned etching between doped fingers

Polycrystalline silicon on silicon oxide (poly-Si/SiO x ) passivating contacts can be used for ultra-high-efficiency interdigitated back contact (IBC) monocrystalline silicon solar cells. We evaluate the use of intrinsic poly-Si for the region that isolates the p- and n-type fingers at the back side of IBC devices. To mitigate shunt across the isolation region between the doped p- and n-type fingers, we demonstrate self-aligned subtractive processing by etching the poly-Si in the isolation region using SF6 plasma followed by etching in a tetramethylammonium hydroxide (TMAH) solution. After removal of the poly-Si, the isolation region was passivated with SiN x and Al 2 O 3 , which resulted in an 11.7% increase in the fill factor in a 19.8% efficient device. Furthermore, we evaluate the limitations of this device through Suns-V oc analysis and simulations using SunSolve and Quokka3 solar cell simulation software. Through Quokka3, we show that the most significant efficiency losses come from junction recombination current (J 02 ) in the isolation region between doped fingers. We predict that the cell efficiency can be most improved with reduced J 02 through better isolation of heavily doped fingers by etching the isolation region deeper into the bulk or through enhanced surface chemical passivation in this region.

14 SOLAR ENERGY↗
DOE OSTI2020

Well-to-Wheels Analysis of Zero-Emission Plug-In Battery Electric Vehicle Technology for Medium- and Heavy-Duty Trucks

Conventional diesel medium- and heavy-duty vehicles (MHDVs) create large amount of air emissions. With the advancement in technology and reduction in the cost of batteries, plug-in battery electric vehicles (BEVs) are increasingly attractive options for improving energy efficiency and reducing air emissions of MHDVs. In this paper, we compared the well-to-wheels (WTW) greenhouse gases (GHGs) and criteria air pollutant emissions of MHD BEVs with their conventional diesel counterparts across weight classes and vocations. We expanded the Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET) model to conduct the WTW analysis of MHDVs. The fuel economy for a wide range of MHDV weight classes and vocations, over various driving cycles, was evaluated using a high-fidelity vehicle dynamic simulation software (Autonomie). The environmental impacts of MHD BEVs are sensitive to the source of electricity used to recharge their batteries. The WTW results show that MHD BEVs significantly improve environmental sustainability of MHDVs by providing deep reductions in WTW GHGs, nitrogen oxides, volatile organic compounds, and carbon monoxide emissions, compared to conventional diesel counterparts. Increasing shares of renewable and natural gas technologies in future national and regional electricity generation are expected to reduce WTW particulate matters and sulfur oxide emissions for further improvement of the environmental performance of MHD BEVs.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Cyber‐physical system testbed for power system monitoring and wide‐area control verification

The electric power system is intrinsically a cyber‐physical system (CPS) with power flowing inthe physical system and information flowing in the cyber‐network. Testbeds arecrucial for understanding the cyber‐physical interactions and provideenvironments for prototyping novel applications. This study proposes afour‐layer architecture for CPS testbeds with emphases on communication networkemulation and networked physical components. A configurable software‐definednetwork is employed to bridge physical components with wide‐area applicationsfor closed‐loop control. In order to distribute physically coupled devices intomultiple software simulations, this study proposes a data broker setup based ona distributed messaging environment to achieve low‐latency data streaming. Thedecoupled design with data streaming allows for building testbed components asmodules and running them in a distributed manner. Case studies verify the databroker setup for low‐latency sensing and actuation, as well as the communicationemulation setup for the desired network latency. Also illustrated is a replayattack scenario using synchrophasors in the Western Electricity CoordinatingCouncil (WECC) 181‐bus system for demonstrating the closed‐loop cyber‐physicalsimulation capability of the testbed.

Cui, Hantao↗
DOE OSTI2024

Accelerating science: The usage of commercial clouds in ATLAS Distributed Computing

The ATLAS experiment at CERN is one of the largest scientific machines built to date and will have ever growing computing needs as the Large Hadron Collider collects an increasingly larger volume of data over the next 20 years. ATLAS is conducting R&D projects on Amazon Web Services and Google Cloud as complementary resources for distributed computing, focusing on some of the key features of commercial clouds: lightweight operation, elasticity and availability of multiple chip architectures. The proof of concept phases have concluded with the cloud-native, vendoragnostic integration with the experiment’s data and workload management frameworks. Google Cloud has been used to evaluate elastic batch computing, ramping up ephemeral clusters of up to O(100k) cores to process tasks requiring quick turnaround. Amazon Web Services has been exploited for the successful physics validation of the Athena simulation software on ARM processors. We have also set up an interactive facility for physics analysis allowing endusers to spin up private, on-demand clusters for parallel computing with up to 4 000 cores, or run GPU enabled notebooks and jobs for machine learning applications. The success of the proof of concept phases has led to the extension of the Google Cloud project, where ATLAS will study the total cost of ownership of a production cloud site during 15 months with 10k cores on average, fully integrated with distributed grid computing resources and continue the R&D projects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗