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At least 757 records · Page 42

Application of the metabolic modeling pipeline in KBase to categorize reactions, predict essential genes, and predict pathways in an isolate genome

The DOE Systems Biology Knowledgebase (KBase) platform offers a range of powerful tools for the reconstruction, refinement, and analysis of genome-scale metabolic models built from microbial isolate genomes. In this chapter, we describe and demonstrate these tools in action with an analysis of isoprene production in the Bacillus subtilis DSM genome. Two different methods are applied to build initial metabolic models for the DSM genome, then the models are gapfilled in three different growth conditions. Next, flux balance analysis (FBA) and flux variability analysis (FVA) techniques are applied to both study the growth of these models in minimal media and classify reactions within each model based on essentiality and functionality. The models are applied with the FBA method to predict essential genes, which are then compared to an updated list of essential genes obtained for B. subtilis 168, a very similar strain to the DSM isolate. The models are also applied to simulate Biolog growth conditions, and these results are compared with Biolog data collected for B. subtilis 168. Finally, the DSM metabolic models are applied to explore the pathways and genes responsible for producing isoprene in this strain. These studies demonstrate the accuracy and utility of models generated from the KBase pipelines, as well as exploring the tools available for analyzing these models.

DOE knowledgebase↗

Physics makes the difference: Bayesian optimization and active learning via augmented Gaussian process

Abstract Both experimental and computational methods for the exploration of structure, functionality, and properties of materials often necessitate the search across broad parameter spaces to discover optimal experimental conditions and regions of interest in the image space or parameter space of computational models. The direct grid search of the parameter space tends to be extremely time-consuming, leading to the development of strategies balancing exploration of unknown parameter spaces and exploitation towards required performance metrics. However, classical Bayesian optimization (BO) strategies based on the Gaussian process (GP) do not readily allow for the incorporation of the known physical behaviors or past knowledge. Here we explore a hybrid optimization/exploration algorithm created by augmenting the standard GP with a structured probabilistic model of the expected system’s behavior. This approach balances the flexibility of the non-parametric GP approach with a rigid structure of physical knowledge encoded into the parametric model. The fully Bayesian treatment of the latter allows additional control over the optimization via the selection of priors for the model parameters. The method is demonstrated for a noisy version of a standard univariate test function used to evaluate optimization algorithms and further extended to physical lattice models. This methodology is expected to be universally suitable for injecting prior knowledge in the form of physical models and past data in the BO framework.

42 ENGINEERING↗

Identifying Order and Disorder in Double Four-Membered Rings via Raman Spectroscopy during Crystallization of LTA Zeolite

Fluoride (F – ) has been essential for the synthesis of low-defect siliceous zeolites. It has been hypothesized that F – balances the positive charges from organic structure-directing agents (OSDAs) and stabilizes key building units during zeolite crystallization such as the double four-membered ring (D4R). However, due to the lack of characterization techniques for investigating medium-range structures, including rings and cages formed during zeolite crystallization, the roles of F – in stabilizing building units and maintaining local charge balance during zeolite assembly are not yet fully understood. Here, the crystallization of siliceous Linde type A (LTA) zeolite in the presence of F – was investigated using Raman spectroscopy and periodic density functional theory (DFT) calculations. We have discovered that the F – -filled double four-membered ring (F – /D4R) and the empty D4R exhibit rather distinct Raman features. Both the F – /D4R and empty D4R are formed in the LTA zeolite synthesized in the presence of F – using 1,2-dimethyl-3-(4-methylbenzyl) imidazolium as the OSDA. Observed Raman bands of the F – /D4R and empty D4R, along with predictive DFT calculations on LTA supercells, reveal an ordered distribution of these two D4R units in the final as-made LTA zeolite. The discovery of these distinct Raman signatures of F – /D4R and empty D4R units opens an interesting new window for studying defects in the D4R during zeolite formation. In particular, we have observed variation in Raman intensities of F – /D4R and empty D4R bands during LTA crystallization; periodic DFT calculations indicate that the observed Raman behavior is consistent with empty D4R units containing one or two Si vacancies surrounded by Q 3 Si—consistent also with solid-state nuclear magnetic resonance measurement. These defects appear to heal during further crystallization, leading to the formation of defect-free LTA zeolite crystals. Altogether, our results provide deeper understanding on the roles of F – in charge balancing and stabilizing intact D4R units during zeolite formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Kaon gluon parton distribution and momentum fraction from 2+1+1 lattice QCD with high statistics

We present a high-statistics lattice-QCD determination of the kaon gluon parton distribution function and gluon momentum fraction. We use clover valence fermion action to take 1,296,640 kaon-correlator measurements on a highly improved staggered quark ensemble with 𝑎 ≈ 0.12 fm and 310-MeV pion mass generated by the MILC Collaboration. A detailed investigation into the impact of gauge-link smearing on the gluonic matrix elements indicates that five steps of hypercubic smearing offer an effective balance between signal quality and preservation of long-distance physics. We report a nonperturbatively renormalized kaon gluon momentum fraction of Math output error at 𝜇 = 2 GeV in the Math output error scheme. Using reduced pseudo-Ioffe-time-distribution matrix elements and pseudo-parton-distribution-function (PDF) matching, we extract the kaon gluon PDF and compare with the prediction from the Dyson-Schwinger equation and with the pion PDF obtained from the same ensemble.

First-principles calculations↗

Improved Architectures and Training Algorithms for Deep Operator Networks

Operator learning techniques have recently emerged as a powerful tool for learning maps between infinite-dimensional Banach spaces. Trained under appropriate constraints, they can also be effective in learning the solution operator of partial differential equations (PDEs) in an entirely self-supervised manner. In this work we analyze the training dynamics of deep operator networks (DeepONets) through the lens of Neural Tangent Kernel theory, and reveal a bias that favors the approximation of functions with larger magnitudes. To correct this bias we propose to adaptively re-weight the importance of each training example, and demonstrate how this procedure can effectively balance the magnitude of back-propagated gradients during training via gradient descent. We also propose a novel network architecture that is more resilient to vanishing gradient pathologies. Taken together, our developments provide new insights into the training of DeepONets and consistently improve their predictive accuracy by a factor of 10-50x, demonstrated in the challenging setting of learning PDE solution operators in the absence of paired input-output observations.

97 MATHEMATICS AND COMPUTING↗

Sequence-to-sequence neural networks for short-term electrical load forecasting in commercial office buildings

The U.S. power grid is transforming to become smarter, cleaner, and more effi- cient. This is leading to the addition of significant distributed variable renew- able generation. Due to the variable nature of renewable generation, the short- and long-term supply-demand imbalances are less predictable, and conventional approaches to mitigating the imbalance will not be efficient or cost-effective. To address this challenge, transactive control technologies have been proposed which balance energy generation and consumption with market activity and in- frastructural limitations. Transactive control requires the ability of individual end-use loads to express flexibility as a function of a transactive signal (e.g., price). Empirical gray- and black-box models have been widely used to express flexibility, and although these approaches are generally easy to construct and simple to use, they do not capture the non-linear behavior that some end-use loads represent . Machine learning approaches have been proposed to address this limitation. Although deep learning approaches for forecasting end-use loads have been explored, certain aspects of the application of deep models to load forecasting are not well understood. These aspects include how much training data is required, and how models should be structured and trained. To that end, this work explores how to approach applying deep recurrent neural networks to short-term electrical load forecasting with a case study of four commercial office buildings. We identify data requirements for training accurate models of whole building electricity use conditioned on outdoor temperature, provide insight into model hyperparameter sensitivity, and demonstrate how readily models can be generalized to unseen buildings.

Skomski, Elliott↗

Structural relaxation of water during rapid cooling from ambient temperatures

Experiments investigating the properties of deeply supercooled liquid water are needed to develop a comprehensive understanding of water’s anomalous properties. One approach involves transiently heating nanoscale water films into the supercooled region for several nanoseconds at a time and then interrogating the water films after they have quenched to cryogenic temperatures. To relate the results obtained with this approach to other experiments and simulations on supercooled water, it is important to understand how closely the quenched structure tracks the (metastable) equilibrium structure of water as a function of the transient heating temperature. A key step involves quantifying the extent to which water that is transiently heated to ambient temperatures [hyperquenched water (HQW)] subsequently relaxes toward the structure of low-density amorphous (LDA) ice as it cools. We analyzed the infrared reflection–absorption spectra of LDA, HQW, and crystalline ice films to determine their complex indices of refraction. With this information, we estimate that HQW retains ~50%–60% of a structural motif characteristic of water at high temperatures with the balance comprised of a low-temperature motif. This result, along with results from x-ray diffraction experiments on water and amorphous ices, allows one to quantify the fraction of the high-temperature motif at approximately zero pressure as a function of temperature from 150 to 350 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational design of high-entropy rare earth aluminum garnets for advanced thermal and environmental barrier coatings

To enhance the protection of Ni-based superalloys in gas turbine engines’ high-temperature environments, it’s crucial to develop advanced thermal/environmental barrier coating (T/EBC) materials with a balanced combination of thermal and mechanical properties. This optimization is essential to safeguard against chemical and thermal challenges. Here, in this study, we harness the power of density functional theory (DFT) in conjunction with combinatorial chemistry methodologies to engineer high-performance high-entropy rare earth disilicates of the RE 3 Al 5 O 12 family (where RE denotes Y, Gd, Er, and Yb). These materials are meticulously designed to exhibit superior phase stability, a targeted coefficient of thermal expansion (CTE), low lattice thermal conductivity, and robust mechanical properties. The determination of CTE values is accomplished through phonon calculations at various volume settings within the quasi-harmonic approximation, while lattice thermal conductivities are rigorously assessed employing the Debye-Callaway model, accounting for three distinct phonon processes. Our findings highlight the remarkable attributes of the solid solution (Y 1/4 Gd 1/4 Er 1/4 Yb 1/4 ) 3 Al 5 O 12 , which displays a reduction in lattice thermal conductivity compared to its individual constituents while maintaining a favorable range of CTE values. The novel T/EBC material, distinguished by their multifaceted functionalities, are poised to use in substantial enhancements in the performance of engines.

36 MATERIALS SCIENCE↗

Data Projection of the High Temperature Electrolysis System in the Dynamic Energy Transport and Integration Laboratory using Dynamic System Scaling

For nuclear power to be flexible in a functioning Integrated Energy System (IES), excess produced heat must be stored or utilized during times of low power demand to ensure a load factor of 1 while load balancing. The Dynamic Energy Transport and Integration Laboratory (DETAIL) is one facility that is under development to emulate IES conditions on the engineering-scale, planned to conduct virtual real time operations with industry-scale facilities, and is currently testing thermal storage and high temperature electrolysis. As part of the study to develop a method to preprocess input signals or postprocess output signals between systems of different scales via Dynamical System Scaling (DSS), the current research is one of the continued efforts branching from the data projection activity conducted for the Thermal Energy Distribution System and currently engages the High Temperature Electrolysis (HTE) System in DETAIL. The HTE SOEC electrical, fluid, and thermal dynamics Figure of Merits (FOM) were identified, governing equations and closure relations were successfully scaled, and relations between FOM scaling ratios were determined. Setting the scaling objectives to reform existing data to project a data set that doubly accelerated the electrolysis process while preserving the produced amount of hydrogen was generated for the full transient. The calculated boundary conditions were inlet temperature, stack current, and inlet steam mass flow rate at 1470 K, 121.1 A, and 1.886 g/s, respectively. The research outcomes demonstrated an output signal postprocessing case accelerating the hydrogen production without changing geometry, number of cells, and partial pressures.

08 HYDROGEN↗

Voltage regulator dissipates minimal power and functions as a voltage divider

Regulator requires minimum amount of power for voltage division and it is not required continuously. The only power loss, except for regulating purposes, is that needed to provide for imbalances in load current requirements. For balanced loads, only leakage current flows through regulating transistors.

Hester, H. B.↗

Optimal guidance for the space shuttle transition.

A guidance method for the space shuttle's transition from hypersonic entry to subsonic cruising flight is presented. The method evolves from a numerical trajectory optimization technique in which kinetic energy and total energy (per unit weight) replace velocity and time in the dynamic equations. This allows the open end-time problem to be transformed to one of fixed terminal energy. In its ultimate form, 'E-Guidance' obtains energy balance (including dynamic-pressure-rate damping) and path length control by angle-of-attack modulation and cross-range control by roll angle modulation. The guidance functions also form the basis for a pilot display of instantaneous maneuver limits and destination. Numerical results illustrate the E-Guidance concept and the optimal trajectories on which it is based.

Stengel, R. F.↗

Optimal guidance for the space shuttle transition

A guidance method for the space shuttle's transition from hypersonic entry to subsonic cruising flight is presented. The method evolves from a numerical trajectory optimization technique in which kinetic energy and total energy (per unit weight) replace velocity and time in the dynamic equations. This allows the open end-time problem to be transformed to one of fixed terminal energy. In its ultimate form, E-Guidance obtains energy balance (including dynamic-pressure-rate damping) and path length control by angle-of-attack modulation and cross-range control by roll angle modulation. The guidance functions also form the basis for a pilot display of instantaneous maneuver limits and destination. Numerical results illustrate the E-Guidance concept and the optimal trajectories on which it is based.

Stengel, R. F.↗

Optimal guidance for the space shuttle transition

A guidance method for the space shuttle's transition from hypersonic entry to subsonic cruising flight is presented. The method evolves from a numerical trajectory optimization technique in which kinetic energy and total energy (per unit weight) replace velocity and time in the dynamic equations. This allows the open end-time problem to be transformed to one of fixed terminal energy. In its ultimate form, E-Guidance obtains energy balance (including dynamic-pressure-rate damping) and path length control by angle-of-attack modulation and cross-range control by roll angle modulation. The guidance functions also form the basis for a pilot display of instantaneous maneuver limits and destination. Numerical results illustrate the E-Guidance concept and the optimal trajectories on which it is based.

Stengel, R. F.↗

Two-temperature accretion disks with electron-positron pairs - Effects of Comptonized external soft photons

The present account of the effects of soft photons from external sources on two-temperature accretion disks in electron-positron pair equilibrium solves the energy-balance equation for a given radial distribution of the input rate of soft photons, taking into account their bremsstrahlung and Comptonization. Critical rate behavior is investigated as a function of the ratio of the energy flux of incident soft photons and the energy-generation rate. As in a previous study, the existence of a critical accretion rate is established.

Kusunose, Masaaki↗

Validation of Spectral Analysis as a Noninvasive Tool to Assess Autonomic Regulation of Cardiovascular Function

A major focus of our program has been to develop a sensitive noninvasive procedure to quantify early weightlessness-induced changes in cardiovascular function or potential dysfunction. Forty studies of healthy young volunteers (10 men and 10 women, each studied twice) were conducted to determine changes in the sympatho-vagal balance of autonomic control of cardiovascular regulation during graded headward and footward blood volume shifts. Changes in sympatho-vagal balance were classified by changes in the mean levels and spectral content of cardiovascular variables and verified by changes in circulating levels of catecholamines and pancreatic polypeptide. Possible shifts in intra/extravascular fluid were assessed from changes in hematocrit and plasma mass density while changes in the stimulus to regulate plasma volume were determined from Plasma Renin Activity (PRA). Autonomic blockade was used to unmask the relative contribution of sympathetic and parasympathetic efferent influences in response to 10 min each of 0, 20 and 40 mmHg Lower Body Negative Pressure (LBNP) and 15 and 30 mmHg Positive Pressure (LBPP). The combination of muscarinic blockade with graded LBNP and LBPP was used to evoke graded increases and decreases in sympathetic activity without parasympathetic contributions. The combination of beta blockade with graded LBNP and LBPP was used to produce graded increases and decreases in parasympathetic activity without beta sympathetic contributions. Finally, a combination of both beta and muscarinic blockades with LBNP and LBPP was used to determine the contribution from other, primarily alpha adrenergic, sources. Mean values, spectral analyses and time frequency analysis of R-R interval (HR), Arterial Pressure (AP), peripheral blood flow (RF), Stroke Volume (SV) and peripheral resistance (TPR) were performed for all phases of the study. Skin blood Flow (SF) was also measured in other studies and similarly analyzed. Spectra were examined for changes in three frequency regions (low 0.006 - 0.005 Hz (LF), mid 0.05 - 0.15 Hz (W), and high 0.15 - 0.45 Hz (EF)). The primary objective of the study was to indicate which changes in the mean values and/or spectra of cardiovascular variables consistently correlated with changes in sympatho-vagal balance in response to headward and footward fluid shifts. A secondaey objective was to quantify the vascular and extravascular fluid shifts evoked by LBNP and LBPP. The principal hypothesis being tested was that headward fluid shifts would evoke an increase in parasympathetic activity and footward fluid shifts would evoke an increase in sympathetic activity both of which would be detected by spectral analysis and verified by circulating hormones. Hematocrit (HCT), plasma mass density and plasma renin activity increased with muscarinic blockade and with LBNP, a response indicative of a plasma shift to extravascular spaces. Beta blockade alone or after muscarinic blockade had no effect on HCT or plasma mass density. With respect to intravascular fluid volume distribution, LBNP and LBPP produced sufficient upper body vascular fluid shifts to evoke appropriate autonomic regulatory responses.

Knapp, Charles F.↗

A Posteriori Error Estimation for Finite Volume and Finite Element Approximations Using Broken Space Approximation

We consider a posteriori error estimates for finite volume and finite element methods on arbitrary meshes subject to prescribed error functionals. Error estimates of this type are useful in a number of computational settings: (1) quantitative prediction of the numerical solution error, (2) adaptive meshing, and (3) load balancing of work on parallel computing architectures. Our analysis recasts the class of Godunov finite volumes schemes as a particular form of discontinuous Galerkin method utilizing broken space approximation obtained via reconstruction of cell-averaged data. In this general framework, weighted residual error bounds are readily obtained using duality arguments and Galerkin orthogonality. Additional consideration is given to issues such as nonlinearity, efficiency, and the relationship to other existing methods. Numerical examples are given throughout the talk to demonstrate the sharpness of the estimates and efficiency of the techniques. Additional information is contained in the original.

Barth, Timothy J.↗

Demonstration of the Space Launch System Augmenting Adaptive Control Algorithm on Pole-Cart Platform

NASA's baseline Space Launch System (SLS) ight control system (FCS) includes an adaptive augmenting control (AAC) portion in addition to the ight-heritage nominal classical controller. The AAC algorithm is intended to improve the robustness and performance of the classical controller. Over the past several years, the AAC algorithm developed at NASA Marshall Space Flight Center (MSFC) has matured significantly through extensive simulation, rigorous analytical proofs, and a series of successful ight tests on a F18 aircraft. This study was part of a SLS program and NASA Engineering and Safety Center (NESC) joint e ort to further increase the confidence level of the AAC algorithm by demonstrating its key functionalities on a classroom type of example, the pole-cart sys- tem, at the NASA Langley Research Center (LaRC) dynamics and control laboratory. The fundamental dynamics behind balancing an inverted pendulum is similar to controlling an aerodynamically unstable rocket. Both systems are inherently open-loop unstable and requires feedback control for attitude stabilization. The principles behind the AAC algorithm is applicable to a wide range of conditionally stable dynamical systems. Hence, the outcomes from this simple and inexpensive exercise has provided the SLS program with additional confidence into the AAC design, operation, robustness, and application.

Pei, Jing↗

SUbsonic Single Aft eNgine (SUSAN) Power/Propulsion System Hardware-in-the-Loop Test Results

Electrified Aircraft Propulsion (EAP) technology offers a promising path forward for reducing greenhouse gas emissions and other negative environmental effects from the commercial aviation sector. EAP systems can reduce fuel burn and improve performance over state-of the-art designs, however the increased complexity and highly coupled nature of these systems present challenges that require new control approaches. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a concept aircraft developed by NASA as a reference design for a commercial transport aircraft with a highly integrated hybrid-electric powertrain. This paper summarizes the results of a Hardware-in-the-Loop (HIL) test of a control architecture developed for the SUSAN power/propulsion system (PPS). The test was performed in the Hybrid Propulsion Emulation Rig (HyPER) facility at the NASA Glenn Research Center (GRC) and involved a real-time reference model of the SUSAN PPS and control system running with a sub-scale electro-mechanical system replacing one of the PPS subsystems. A side-by-side comparison of the simulated and real systems in the HIL test results shows that the control architecture functions well in both the simulation and the real-time HIL environment. In both cases the controller is able to simultaneously deliver the required thrust response and balance power levels between the electrical and turbomachinery subsystems.

Jonah J Sachs-Wetstone↗