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At least 127 records · Page 7

Analysis of Rig Parameter Data Using Drilling Process Modeling Constraints, Volume 5: Utah FORGE Well 16B(78)-32

Drill rig parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. While insightful into the drilling process, these measurements are of reduced value without a standard to aid in data evaluation and decision making. In the main body of this work (Volume 1), a method is demonstrated whereby rock reduction model constraints are used to interpret drilling response parameters; the method could be applied in real-time to improve decision-making in the field and to further discern technology performance during post-drilling evaluations. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) in computational algorithms. The method presented has applicability to development of advanced analytics on future geothermal wells using real-time electronic data recording for improved performance and reduced drilling costs. A drilling cost model is also used to show the tradeoff between rate of penetration and bit life and the influence on interval drilling costs. Details of the bit specifications and performance are cataloged in an independent volume, documented under separate cover, for each of the four wells, and include Volume 2: Utah FORGE 16A(78)-32; Volume 3: Utah FORGE 56-32; Volume 4: Utah FORGE 78B-32 and Volume 5: Utah FORGE 16B(78)-32.

15 GEOTHERMAL ENERGY↗

Analysis of Rig Parameter Data Using Drilling Process Modeling Constraints, Volume 4: Utah FORGE Well 78B-32

Drill rig parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. While insightful into the drilling process, these measurements are of reduced value without a standard to aid in data evaluation and decision making. In the main body of this work (Volume 1), a method is demonstrated whereby rock reduction model constraints are used to interpret drilling response parameters; the method could be applied in real-time to improve decision-making in the field and to further discern technology performance during post-drilling evaluations. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) in computational algorithms. The method presented has applicability to development of advanced analytics on future geothermal wells using real-time electronic data recording for improved performance and reduced drilling costs. A drilling cost model is also used to show the tradeoff between rate of penetration and bit life and the influence on interval drilling costs. Details of the bit specifications and performance are cataloged in an independent volume, documented under separate cover, for each of the four wells, and include Volume 2: Utah FORGE 16A(78)-32; Volume 3: Utah FORGE 56-32; Volume 4: Utah FORGE 78B-32 and Volume 5: Utah FORGE 16B(78)-32.

15 GEOTHERMAL ENERGY↗

Analysis of Rig Parameter Data Using Drilling Process Modeling Constraints, Volume 3: Utah FORGE Well 56-32

Drill rig parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. While insightful into the drilling process, these measurements are of reduced value without a standard to aid in data evaluation and decision making. In the main body of this work (Volume 1), a method is demonstrated whereby rock reduction model constraints are used to interpret drilling response parameters; the method could be applied in real-time to improve decision-making in the field and to further discern technology performance during post-drilling evaluations. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) in computational algorithms. The method presented has applicability to development of advanced analytics on future geothermal wells using real-time electronic data recording for improved performance and reduced drilling costs. A drilling cost model is also used to show the tradeoff between rate of penetration and bit life and the influence on interval drilling costs. Details of the bit specifications and performance are cataloged in an independent volume, documented under separate cover, for each of the four wells, and include Volume 2: Utah FORGE 16A(78)-32; Volume 3: Utah FORGE 56-32; Volume 4: Utah FORGE 78B-32 and Volume 5: Utah FORGE 16B(78)-32.

15 GEOTHERMAL ENERGY↗

Analysis of Rig Parameter Data Using Drilling Process Modeling Constraints, Volume 1: Summary of Utah FORGE Wells 16A(78)-32, 56-32, 78B-32 and 16B(78)-32

Drill rig parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. While insightful into the drilling process, these measurements are of reduced value without a standard to aid in data evaluation and decision making. In the main body of this work (Volume 1), a method is demonstrated whereby rock reduction model constraints are used to interpret drilling response parameters; the method could be applied in real-time to improve decision-making in the field and to further discern technology performance during post-drilling evaluations. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) in computational algorithms. The method presented has applicability to development of advanced analytics on future geothermal wells using real-time electronic data recording for improved performance and reduced drilling costs. A drilling cost model is also used to show the tradeoff between rate of penetration and bit life and the influence on interval drilling costs. Details of the bit specifications and performance are cataloged in an independent volume, documented under separate cover, for each of the four wells, and include Volume 2: Utah FORGE 16A(78)-32; Volume 3: Utah FORGE 56-32; Volume 4: Utah FORGE 78B-32 and Volume 5: Utah FORGE 16B(78)-32.

15 GEOTHERMAL ENERGY↗

Sensor Recommendations for Long Term Monitoring of the F-Area Seepage Basins

In mid-2018, a new paradigm for long-term monitoring was developed after of decade of applied research projects funded by the Department of Energy’s office of Environmental Management Technology Development program. The program at SRNL was focused on transitioning complex environmental waste sites from active to passive remediations strategies. A key result of these studies was that the use of enhanced attenuation approaches at radiologically contaminated sites will result in the creation of secondary source areas in the subsurface that will require monitoring for decades. Alternative monitoring approaches are being developed and tested at the Savannah River Site’s F-Area Hazardous Waste Management Facility, the new paradigm provides innovative solutions that will significantly lower costs of monitoring through the coupling of data collection, machine learning and deterministic groundwater modeling. The foundation of this approach is a well-optimized network of sensors for measuring hydrogeochemical master variables that control, and therefore act as indicators of groundwater contaminant transport. By monitoring changes in the controlling master variables over time arising from geological and environmental shifts, predictive modelling can assist with identifying new strategies for ensuring regulatory requirements are met if trends toward conditions for potential remobilization of attenuated contaminants are detected. In this report, we evaluated commercially available single parameter sensor platforms (e.g., temperature/depth) and configurable multi-parameter sensor platforms (e.g., pH, oxidation-reduction potential, temperature, depth, dissolved oxygen, and conductivity). Each was scored using an optimization function based on how well the system supports the proposed long-term monitoring paradigm, in general, and the site-specific conditions at F-Area, in particular. Several viable sensor systems were identified. Of these, a combined platform including the In-Situ Aqua TROLL 500 multi-parameter sensor platform and the In-Situ temperature/depth sensor had the highest rating and was identified as the most suitable candidate for installation and monitoring of the master variables and potentiometric surface that control groundwater contaminant plumes emanating from the F-Area Seepage Basins. The discussion of recommended potential deployment locations builds upon recommendations made by Denham et al (2019).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Quantification of Swelling in Hematite Pellets Reduced Using Hydrogen–Nitrogen Gas Mixture

Iron ore pellets are reduced in a 50%H 2 –50%N 2 1 atm gas mixture at 750, 800, 850, 900, and 950 °C while simultaneously documenting swelling (change in pellet radius) and weight change. Swelling increases with increasing temperature, with catastrophic swelling (>20% of reduction swelling index) observed at 850, 900, and 950 °C. As the pellet is reduced, the pellet radius increases until 40–50% reduction is achieved, followed by a decrease in diameter beyond 40–50% reduction at 750 and 850 °C. At 950 °C, the pellet radius continues to increase with additional pellet reduction without any subsequent decrease in diameter. Scanning electron microscopy (SEM) analysis shows that the neighboring grains inside the pellet sinter together at 750 and 850 °C, whereas the individual grains sinter internally at 950 °C. SEM analysis and observations suggest that the reduction process at 750 and 850 °C can be approximated as a topochemical reaction process, while the reduction process at 950 °C can no longer be approximated as a topochemical reaction process. In conclusion, an empirical equation for the radius of the pellet is derived with fitting parameters dependent on temperature and the degree of reduction of the pellet undergoing reduction based on the experimental data.

08 HYDROGEN↗

Mechanistic Insights into Dinitrogen Reduction to Ammonia in Light-Controlled Nanocrystal:Nitrogenase Complexes

Developing systems that can efficiently capture photon energy and convert this energy into fuels and chemicals requires understanding how to assemble molecular components with diverse functions into complete systems possessing selectivity and efficiency in directing charge carriers to catalytic reactions. There are many challenges to achieving this goal. One promising approach is the development of hybrid systems that combine semiconductor nanocrystals (NCs) for light capture and enzymes as efficient catalysts. Such biohybrid systems capitalize on the tunable electronic and optical properties of NCs while leveraging the unmatched specificity and efficiency of enzymes in catalyzing chemical reactions, thereby offering opportunities to surpass the limitations of each component alone. Here, we focus on recent progress in developing a biohybrid system that combines CdS NCs for photon capture with the enzyme nitrogenase to accomplish light-driven dinitrogen (N 2 ) reduction to ammonia (NH 3 ). Integrating light-harvesting materials with biological catalysts requires a deep understanding of NC properties, protein stability, and electron transfer (ET), making it an inherently multidisciplinary problem. The reduction of N 2 to NH 3 is a challenging reaction, with a high demand in both agriculture and industrial chemical production. This reaction is intrinsically energy intensive, due to the need to activate the N≡N triple bond. The current standard industrial approach to N 2 reduction, the Haber−Bosch reaction, obtains the necessary energy input from fossil fuels, whereas biological systems capable of N 2 reduction utilize the hydrolysis of ATP as their energy source. Replacing these costly, energy-intensive inputs with renewable light energy represents a critical step toward sustainable NH 3 production. Recent progress has demonstrated that semiconductor CdS NCs can be coupled to the catalytic component of nitrogenase, the MoFe protein, to form a biohybrid CdS NC:MoFe protein complex, enabling light-driven N 2 reduction rather than energy input from fossil fuels or ATP. This illustrates how inorganic NCs can functionally replace the natural Fe protein partner, yielding a biohybrid catalyst that enables controlled electron delivery and provides not only light-driven NH 3 production but also new approaches for probing enzyme catalytic function. The CdS NC:MoFe protein biohybrid system enables light-initiated electron delivery at ambient temperature, as well as temperatures below freezing, allowing for stabilization and spectroscopic characterization of key reaction intermediates. These findings highlight how photochemical biohybrids can serve as both functional catalysts and mechanistic probes. Beyond studies of the nitrogenase mechanism, studies of the CdS NC:MoFe system reveal how variables such as NC size, electrostatic binding interactions, and sacrificial electron donors (SEDs) govern complex stability, charge transfer efficiency, and catalytic performance. In addition, studies of nitrogenase and the high activation barrier for N 2 reduction are enabling investigations of new and interesting questions regarding the properties and limitations of NC biocatalysis. In this Account, we describe the key features of CdS NC:MoFe protein biohybrids and the parameters for optimal light-driven N 2 reduction, and how controlling ET with light illuminates the path to new insights into the nitrogenase mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Influences of pH and substrate supply on the ratio of iron to sulfate reduction

Iron reduction and sulfate reduction often occur simultaneously in anoxic systems, and where that is the case, the molar ratio between the reactions (i.e., Fe/SO 4 2- reduced) influences their impact on water quality and carbon storage. Previous research has shown that pH and the supply of electron donors and acceptors affect that ratio, but it is unclear how their influences compare and affect one another. This study examines impacts of pH and the supply of acetate, sulfate, and goethite on the ratio of iron to sulfate reduction in semi-continuous sediment bioreactors. We examined which parameter had the greatest impact on that ratio and whether the parameter influences depended on the state of each other. Results show that pH had a greater influence than acetate supply on the ratio of iron to sulfate reduction, and that the impact of acetate supply on the ratio depended on pH. In acidic reactors (pH 6.0 media), the ratio of iron to sulfate reduction decreased from 3:1 to 2:1 as acetate supply increased (0-1 mM). In alkaline reactors (pH 7.5 media), iron and sulfate were reduced in equal proportions, regardless of acetate supply. Secondly, a comparison of experiments with and without sulfate shows that the extent of iron reduction was greater if sulfate reduction was occurring and that the effect was larger in alkaline reactors than acidic reactors. Thus, the influence of sulfate supply on iron reduction extent also depended on pH and suggests that iron reduction grows more dependent on sulfate reduction as pH increases. Our results compare well to trends in groundwater geochemistry and provide further evidence that pH is a major control on iron and sulfate reduction in systems with crystalline (oxyhydr)oxides. pH not only affects the ratio between the reactions but also the influences of other parameters on that ratio.

59 BASIC BIOLOGICAL SCIENCES↗

Gradient-based constrained optimization using a database of linear reduced-order models

A methodology grounded in model reduction is presented for accelerating the gradient-based solution of a family of linear or nonlinear constrained optimization problems where the constraints include at least one linear Partial Differential Equation (PDE). A key component of this methodology is the construction, during an offline phase, of a database of pointwise, linear, Projection-based Reduced-Order Models (PROM)s associated with a design parameter space and the linear PDE(s). A parameter sampling procedure based on an appropriate saturation assumption is proposed to maximize the efficiency of such a database of PROMs. A real-time method is also presented for interpolating at any queried but unsampled parameter vector in the design parameter space the relevant sensitivities of a PROM. The practical feasibility, computational advantages, and performance of the proposed methodology are demonstrated for several realistic, nonlinear, aerodynamic shape optimization problems governed by linear aeroelastic constraints.

97 MATHEMATICS AND COMPUTING↗

Innovations in optimization and control of accelerators using methods of differential geometry and genetic algorithms (Final Report)

Online tuning of particle accelerators is necessary in order to achieve optimal machine performance. However, it is also a major challenge due to the large parameter space which must be searched and the fact that many of the desir- able objectives compete with one another, and so will not reach their optimal values simultaneously. In order to mitigate these issues, we have explored using dimension-reduction techniques to reduce the size of the parameter space which must be searched and multi-objective genetic algorithms to obtain the sets of tuning parameters which provide pareto-optimal values for the objectives. These methods have enabled us to obtain improved values of the vertical emittance at the Cornell Electron Storage Ring (CESR), and to do so with greater control of orbit errors. Algorithmic tuning is a multidisciplinary endeavour, requiring expertise in beam dynamics, diagnostics, control systems and computer science, and thus a key practical problem is to formulate a common language in which experts with different specialties can communicate. We developed a solution to this problem in the form of a generic accelerator software interface that allows for rapid prototyping of optimization and control algorithms. Our interface is built on the Experimental Physics and Industrial Control Systems (EPICS) and makes possible testing control code in simulation before deployment on real accelerators, as well as deployment of third-party optimization code.

43 PARTICLE ACCELERATORS↗

Evaluating the Performance of Integer Sum Reduction in SYCL on GPUs

SYCL is a promising programming model for heterogeneous computing—allowing a single-source code to target devices from multiple vendors. One significant task performed on these accelerators is a primitive operation for integer sum reduction. This paper presents several SYCL implementations of integer sum reduction—using atomic functions, shared local memory, vectorized memory accesses and parameterized workload sizes—to compare the performance and maturity of SYCL against open-source vendor-specific implementations of the same reduction. For a sufficiently large number of integers, tuning the parameters of our SYCL implementations achieves 1.4X speedup over the open-source implementations on an Intel UHD630 integrated GPU. The SYCL reduction is 3% faster than the templated reduction in Thrust, and 0.3% faster than the device reduction in CUB on an Nvidia P100 GPU. The SYCL reduction is 1.9% faster than the templated reduction in Thrust, and 0.4% faster than the device reduction in CUB on an Nvidia V100 GPU.

Jin, Zheming↗

Estimation of distributions via multilevel Monte Carlo with stratified sampling

We design and implement a novel algorithm for computing a multilevel Monte Carlo (MLMC) estimator of the joint cumulative distribution function (CDF) of a vector-valued quantity of interest in problems with random input parameters and initial conditions. Our approach combines MLMC with stratified sampling of the input sample space by replacing standard Monte Carlo at each level with stratified Monte Carlo initialized with proportionally allocated samples. We show that the resulting stratified MLMC (sMLMC) algorithm is more efficient than its standard MLMC counterpart due to the additional variance reduction provided by the stratification of the random parameter's domain, especially at the coarsest levels. Additional computational cost savings are obtained by smoothing the indicator function with a Gaussian kernel, which proves to be an efficient and robust alternative to recently developed polynomial-based techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Decoding the Mechanisms of Phase Transitions from In Situ Microscopy Observations

Abstract Analysis of the temperature‐ and stimulus‐dependent imaging data toward elucidation of the physical transformations is an ubiquitous problem in multiple fields. Here, temperature‐induced phase transition in BaTiO 3 is explored using the machine learning analysis of domain morphologies visualized via variable‐temperature scanning transmission electron microscopy (STEM) imaging data. This approach is based on the multivariate statistical analysis of the time or temperature dependence of the statistical descriptors of the system, derived in turn from the categorical classification of observed domain structures or projection on the continuous parameter space of the feature extraction‐dimensionality reduction transform. The proposed workflow offers a powerful tool for the exploration of the dynamic data based on the statistics of image representation as a function of the external control variable to visualize the transformation pathways during phase transitions and chemical reactions. This can include the mesoscopic STEM data as demonstrated here, but also optical, chemical imaging, etc., data. It can further be extended to the higher dimensional spaces, for example, analysis of the combinatorial libraries of materials compositions.

Valleti, Sai Mani Prudhvi↗

A redox model for NO oxidation, NH 3 oxidation and high temperature standard SCR over Cu-SSZ-13

A kinetic model is developed to predict the influence of temperature and hydrothermal aging on the redox of active Cu sites under standard SCR, NO oxidation and NH 3 oxidation conditions over a practically relevant fully-formulated Cu-SSZ-13 catalyst. NO 2 /N 2 production during NO/NH 3 titration of Cu II sites is utilized to identify rate parameters associated with NO-only RHC (reduction half cycle) and NH 3 -only RHC respectively. Integral N 2 formation during subsequent NO + NH 3 titration is consistent with the production of one NO 2 per two CuII sites reduced during NO-only RHC and one N 2 per six Cu II sites reduced during NH 3 -only RHC. Decreased reduction of Cu II sites by NO/NH 3 upon hydrothermal aging, along with the production of one NO 2 per two CuII sites during NO-only RHC, is accordant with the involvement of proximal ZCuOH and oxygen-bridged dimeric Cu II sites. Oxidation of partially solvated and framework coordinated ZCu (Cu I ) sites occurs in presence of O 2 , does not produce N 2 and can lead to the consumption of Brønsted acid sites. A global OHC kinetic model is developed to predict transient and integral N 2 formation during exposure of CuI sites to a mixture of NO and O 2 . The resulting redox kinetic model quantitatively predicts NO and NH 3 consumption during isothermal transient response Cu redox (TRCR) protocols, along with temperature and age dependent steady-state standard SCR and oxidation conditions. The redox model presented in this work synthesizes recent kinetic, spectroscopic and computational findings to provide a foundational description of active site redox during standard SCR, NO oxidation and NH3 oxidation over Cu-SSZ-13.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identifying Disadvantaged Communities in the United States: An Energy-Oriented Mapping Tool that Aggregates Environmental and Socioeconomic Burdens

This paper defines a policy-relevant nationwide composite index to identify communities disproportionately impacted by environmental, energy, and climate injustices in the United States. We review existing vulnerability indicators and indices to assess the tradeoffs of different design parameters, including variable selection, geographic unit, dimensionality reduction, weighting, and aggregation methods. From this methodological review, we create the first nationwide, census tract-level index of cumulative burden that includes energy-relevant indicators alongside climate, social, environmental, and economic indicators, and is flexible to the inclusion of additional data sources. We provide a summary of the sources of inputs used to develop a definition for "disadvantaged communities" that can be used to prioritize energy investments. We discuss use-cases for this index including the implementation of the Justice40 Initiative, which calls for 40% of certain federal clean energy benefits to flow to disadvantaged communities in the United States. We use our results to examine historic allocations of federal energy investments and show that communities that we identify as disadvantaged received about 37% fewer funds per capita than non-disadvantaged communities.

cumulative burden↗

Redox-stable symmetrical solid oxide fuel cells with exceptionally high performance enabled by electrode/electrolyte diffuse interface

Here, in this study, we report a high performance and redox-stable symmetrical solid oxide fuel cell (SOFC) based on (Ba 0.5 Sr 0.5 ) (Mo 0.1 Fe 0.9 )O 3-δ (BSMF) electrode and La 0.8 Sr 0.2 Ga 0.8 Mg 0.2 O 3-δ (LSGM) electrolyte. BSMF is able to operate both as anode and cathode. Excellent electrocatalytic activity has been achieved on BSMF towards hydrogen oxidation and oxygen reduction. Due to its closely matched lattice parameter to LSGM electrolyte, a unique diffuse interface is formed between BSMF and LSGM. Compared to a clean interface, e.g. BSMF/gadolinium doped ceria interface, this diffuse interface promotes the performance of BSMF electrode 1–1.8 times in 600–800 °C. Polarization resistance of the BSMF/LSGM specimen is as low as 0.047 and 0.007 Ωcm 2 in humidified H 2 and in air at 800 °C, respectively. On the BSMF/LSGM/BSMF symmetrical cell, a maximum power density of 2.28 W/cm 2 is achieved at 800 °C, the highest among with redox-stable ceramic electrodes to the best of our knowledge. Redox stability of this cell is confirmed. The role of anode and cathode is reversed back and forth in different operation modes. No apparent degradation is observed through 4 cycles within a 110 h operation period. These findings demonstrate that (Ba 0.5 Sr 0.5 ) (M o0.1 Fe 0.9 )O 3-δ coupled with LSGM electrolyte is an excellent choice to build a high performance, redox-stable SOFC.

25 ENERGY STORAGE↗

Initial transient stage of pin-to-pin nanosecond repetitively pulsed discharges in air

In this work, evolution of parameters of nanosecond repetitively pulsed (NRP) discharges in pin-to-pin configuration in air was studied during the transient stage of initial 20 discharge pulses. Gas and plasma parameters in the discharge gap were measured using coherent microwave scattering, optical emission spectroscopy, and laser Rayleigh scattering for NRP discharges at repetition frequencies of 1, 10, and 100 kHz. Memory effects (when perturbations induced by the previous discharge pulse would not decay fully until the subsequent pulse) were detected for the repetition frequencies of 10 and 100 kHz. For 10 kHz NRP discharge, the discharge parameters experienced significant change after the first pulse and continued to substantially fluctuate between subsequent pulses due to rapid evolution of gas density and temperature during the 100 μs inter-pulse time caused by intense redistribution of the flow field in the gap on that time scale. For 100 kHz NRP discharge, the discharge pulse parameters reached a new steady-state at about five pulses after initiation. Further, this new steady-state was associated with well-reproducible parameters between the discharge pulses and substantial reduction in breakdown voltage, discharge pulse energy, and electron number density in comparison to the first discharge pulse. For repetition frequencies 1–100 kHz considered in this work, the memory effects can be likely attributed to the reduction in gas number density and increase in the gas temperature that cannot fully recover to ambient conditions before subsequent discharge pulses.

42 ENGINEERING↗

Spin Squeezing by Rydberg Dressing in an Array of Atomic Ensembles

Here, we report on the creation of an array of spin-squeezed ensembles of cesium atoms via Rydberg dressing, a technique that offers optical control over local interactions between neutral atoms. We optimize the coherence of the interactions by a stroboscopic dressing sequence that suppresses super-Poissonian loss. We thereby prepare squeezed states of N = 200 atoms with a metrological squeezing parameter ξ 2 = 0.77⁢(9) quantifying the reduction in phase variance below the standard quantum limit. We realize metrological gain across three spatially separated ensembles in parallel, with the strength of squeezing controlled by the local intensity of the dressing light. Our method can be applied to enhance the precision of tests of fundamental physics based on arrays of atomic clocks and to enable quantum-enhanced imaging of electromagnetic fields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗