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At least 487 records · Page 27

Formulation and calibration of two-dimensional constitutive models for composite structures based on panel tests

Steel Plate Concrete (SC) composite members have been widely adopted because of its cost-efficiency and enhanced structural behavior. While researchers have attempted to study its in-plane shear behavior in the past twenty years, very limited number of large-scale pure shear tests were performed due to the challenge of experimental set-up and the availability of facilities. In this paper, a series of uniaxial loading tests and two full-scale pure shear panel tests of SC members were reported, on which the “mechanics-based Membrane Model of SC elements (MM-SC)” is developed. The MM-SC model is based on the fixed-angle crack formulation and the smeared-crack formulation, in which the experimental-based uniaxial constitutive models are implemented, considering the local buckling of faceplate, the tension stiffening of steel plate, the strength degradation of cracked concrete and the confinement effect of concrete. The proposed MM-SC model is subsequently incorporated into the object-oriented software OpenSEES. Finally, the simulation results of proposed model well predict the SC test observations in terms of critical branch points and structural behaviors, including initial stiffness, cracking strength, post-crack stiffness, yield strength, maximum strength, and failure modes.

42 ENGINEERING↗

Controlled dehumidification to extract clean water from a multicomponent gaseous mixture of organic contaminants

Rapid expansion of the unconventional oil and gas extraction has increased American energy independence, but also led to increased production of large amounts of contaminated water. Wastewater from the oil and gas industry contains a wide range of contaminants. Injecting such contaminated water into disposal wells or discharging it to the environment jeopardizes freshwater resources. Conventional and membrane-based wastewater treatment techniques are often not effective choices to treat highly contaminated wastewater; however, a suitable way to remove contaminants from wastewater is to selectively separate water in a process analogous to humidification-dehumidification (HDH). Only a few studies have investigated the use of HDH for wastewater treatment. In this study, a novel HDH system is introduced for treating highly contaminated water, such as oil and gas flowback and produced water. In this HDH process, a non-condensable gas, such as air, mixes with wastewater vapor to facilitate the separation of contaminants. As a result, clean water condenses from the multicomponent gaseous mixture while air carries organic contaminants out of the dehumidification section. A laboratory apparatus was constructed and experiments were performed to investigate the HDH process for wastewater treatment and to study the effects of flow dynamics including air flow rate on the composition of treated water. Different contaminants including benzene, toluene, 2-propanol and 2-butoxyethanol were tested. Experimental results showed that the system can be successfully applied for removing volatile and/or toxic organic contaminants from wastewater. A representative multicomponent mixture of fracking wastewater was successfully treated using the experimental setup and clean water with quality of 98.3% was obtained. It was revealed that increasing the air-to-vapor mass ratio improves purity of treated water. Quantitative analysis showed that by increasing the air-to-vapor mass ratio from 0.6 to 5.9, the fraction of separated 2-propanol through the air was improved from 43% to more than 96% of the initial amount. ASPEN software was employed to simulate equilibrium conditions. Finally, experimental results were observed to have lower mass fraction of residual contaminant in the treated water compared to equilibrium state.

42 ENGINEERING↗

Using a Coarse-Grained Modeling Framework to Identify Oligomeric Motifs with Tunable Secondary Structure

Coarse-grained modeling can be used to explore general theories that are independent of specific chemical detail. In this paper, we present cg_openmm, a Python-based simulation framework for modeling coarse-grained hetero-oligomers and screening them for structural and thermodynamic characteristics of cooperative secondary structures. cg_openmm facilitates the building of coarse-grained topology and random starting configurations, setup of GPU-accelerated replica exchange molecular dynamics simulations with the OpenMM software package, and features a suite of postprocessing thermodynamic and structural analysis tools. In particular, native contact analysis, heat capacity calculations, and free energy of folding calculations are used to identify and characterize cooperative folding transitions and stable secondary structures. In this work, we demonstrate the capabilities of cg_openmm on a simple 1–1 Lennard-Jones coarse-grained model, in which each residue contains 1 backbone and 1 side-chain bead. By scanning both nonbonded and bonded force-field parameter spaces at the coarse-grained level, we identify and characterize sets of parameters which result in the formation of stable helices through cooperative folding transitions. Furthermore, we show that the geometries and stabilities of these helices can be tuned by manipulating the force-field parameters.

36 MATERIALS SCIENCE↗

Adapting the Electron Beam from SEM as a Quantitative Heating Source for Nanoscale Thermal Metrology

The electron beam (e-beam) in the scanning electron microscopy (SEM) provides an appealing mobile heating source for thermal metrology with spatial resolution of ~1 nm, but the lack of systematic quantification of the e-beam heating power limits such application development. Here, we systemically study e-beam heating in LPCVD silicon nitride (SiN x ) thin-films with thickness ranging from 200 to 500 nm from both experiments and complementary Monte Carlo simulations using the CASINO software package. There is good agreement about the thickness-dependent e-beam energy absorption of thin-film between modeling predictions and experiments. Using the absorption results, we then demonstrate adapting the e-beam as a quantitative heating source by measuring the thickness-dependent thermal conductivity of SiN x thin-films, with the results validated to within 7% by a separate Joule heating experiment. The results described here will open a new avenue for using SEM e-beams as a mobile heating source for advanced nanoscale thermal metrology development.

42 ENGINEERING↗

Electrochemically Engineered, Highly Energy-Efficient Conversion of Ethane to Ethylene and Hydrogen below 550 °C in a Protonic Ceramic Electrochemical Cell

Ethylene is one of the largest building blocks in the petrochemical industry, mainly produced by steam cracking of ethane derived from naphtha or shale gas at high temperatures (>800 °C). Despite its technical maturity and economic competitiveness, the thermal steam cracking of ethane is highly energy-intensive. In this work, an electrochemically engineered direct conversion process of ethane to produce hydrogen and ethylene using a planar protonic ceramic membrane reactor with a bi-functional three-dimensional catalytic electrode is reported, with a single-pass ethane conversion of 40% and ethylene yield of 26.7% at 550 °C. Compared with the industrial ethane steam cracking, this method saves process energy input by 45.1% and improves process energy efficiency by 50.6%, based on comprehensive process simulation using Aspen Plus software. Further, steam electrolysis treatment under the solid oxide electrolysis cell mode can regenerate the system’s catalytic performance and significantly alleviate catalytic degradation by 74%, demonstrating high techno-economic viability.

bi-functional electrode↗

Special Topic on High Performance Computing in Chemical Physics

Computational modeling and simulation have become indispensable scientific tools in virtually all areas of chemical, biomolecular, and materials systems research. Computation can provide unique and detailed atomic level information that is difficult or impossible to obtain through analytical theories and experimental investigations. In addition, recent advances in micro-electronics have resulted in computer architectures with unprecedented computational capabilities, from the largest supercomputers to common desktop computers. In conclusion, combined with the development of new computational domain science methodologies and novel programming models and techniques, this has resulted in modeling and simulation resources capable of providing results at or better than experimental chemical accuracy and for systems in increasingly realistic chemical environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Micromachined ceramic-based chipless LC resonator for high-temperature wireless sensing applications in harsh environments

The primary objective of this work was the fabrication and testing of a wireless LC resonator based on micro-patterned electroceramic materials for the monitoring of high-temperature systems. The twodimensional planar LC resonator sensors were designed and simulated using ANSYS Maxwell software, and these sensors were then fabricated from electrically conductive La 2 NiO 4 /Al 2 O 3 particulate inks. Initially, the phases of La 2 NiO 4 /Al 2 O 3 composite were evaluated by XRD. The patterning and deposition of the ink were completed using a novel micro-casting process onto Al 2 O 3 ceramic substrates, and the final pattern was bonded onto the substrate at 1200 °C for 2 h. The features and the reliability were analyzed by SEM microscopy. The frequency shift with respect to temperature was measured, which is directly related to changes in the sensor’s dielectric permittivity and pattern dimensions. The sensors were characterized at 500 °C–1000 °C in an ambient atmosphere with an RF signal ranging from 10–80 MHz at 175 kHz·s –1 sweep rate. The sensors showed a sensitivity of ~350 kHz °C –1 from 500 °C–1000 °C. Here, a new robust and adaptive signal processing approach was introduced to increase the degree of freedom for analyzing wireless sensors.

42 ENGINEERING↗

Optimizing the Internal Cell Structure of the Radon Monitor Based on Electrostatic Collection Method

Abstract As Rn-222 decays, an alpha particle is emitted and the residual polonium nucleus recoils in the opposite direction. At the end of the recoil path, 88% of the polonium atoms have a positive charge and 12% are neutral. The electric potential distribution in the 60 ml hemispherical internal cell of the radon monitor based on electrostatic collection is studied for reducing the combined probability of the positively charged Po-218 and the OH− produced by the ionization of water vapour in the air. The COMSOL software is used to simulate the electric potential distribution in the internal cell of the radon monitor based on the electrostatic collection method at 27°C, a pressure of 0.1 Mpa. For improving the collection efficiency of Po-218 ions, the average collection time along vertical and oblique lines is calculated when the upper surface of the internal cell is plastic, uncharged metal and charged metal, respectively. Assuming that the gas in the internal cell is uniformly distributed, the results show that if the upper surface of the hemispherical internal cell is plastic or uncharged metal, the electric potential formed in the internal cell is more uniform, and it is beneficial to reduce the total collection time of the positively charged Po-218 ions, thereby improving collection efficiency. The simulation results can be used as an effective reference for optimizing the design of the internal cell structure of the radon monitor based on electrostatic collection method.

Fan, Zhongkai (ORCID:0000000181247459)↗

Alternative approach to quantum imaginary time evolution

There is increasing interest in quantum algorithms (QAs) that are based on the imaginary time evolution (ITE), a successful classical numerical approach to obtain ground states. However, most of the proposals so far require heavy postprocessing computational steps on a classical computer, such as solving linear equations. Here we provide an alternative approach to implement ITE. A key feature in our approach is the use of an orthogonal basis set: the propagated state is efficiently expressed in terms of orthogonal basis states at every step of the evolution. We argue that the number of basis states needed at those steps to achieve an accurate solution can be kept on the order of n , the number of qubits, by controlling the precision (number of significant digits) and the imaginary time increment. The number of quantum gates per imaginary time step is estimated to be polynomial in n . Additionally, while in many QAs the locality of the Hamiltonian is a key assumption, in our algorithm this restriction is not required. This characteristic of our algorithm renders it useful for studying highly nonlocal systems, such as the occupation-representation nuclear shell model. Here, we illustrate our algorithm through numerical implementation on an IBM quantum simulator.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

JETSCAPE framework: p+p results

The JETSCAPE framework is a modular and versatile Monte Carlo software package for the simulation of high energy nuclear collisions. In this work we present a new tune of JETSCAPE, called PP19, and validate it by comparison to jet-based measurements in p + p collisions, including inclusive single jet cross sections, jet shape observables, fragmentation functions, charged hadron cross sections, and dijet mass cross sections. These observables in p+p collisions provide the baseline for their counterparts in nuclear collisions. Quantifying the level of agreement of JETSCAPE results with p+p data is thus necessary for meaningful applications of JETSCAPE to A+A collisions. The calculations use the JETSCAPE PP19 tune, defined in this paper, based on version 1.0 of the JETSCAPE framework. For the observables discussed in this work calculations using JETSCAPE PP19 agree with data over a wide range of collision energies at a level comparable to standard Monte Carlo codes. These results demonstrate the physics capabilities of the JETSCAPE framework and provide benchmarks for JETSCAPE users.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Hardware-based Advanced Electromagnetic Transient Simulation for A Large-Scale PV Plant in Real Time Digital Simulator

Power electronics-based resources, such as high-voltage direct current (HVdc) substations, photovoltaic (PV) plants, wind plants, electric vehicle charging stations, and energy storage systems, are increasingly being integrated within the power grid. Recently, multiple reports have emphasized the necessity for high-fidelity electromagnetic transient (EMT) simulations of these large-scale power electronics-based resources to accurately understand their behavior in power grids. However, performing hardware-based EMT simulations with high-fidelity models for such large power electronics systems is challenging due to the small time-step requirements and the involvement of a large number of states. This paper presents the implementation of hardware-based high-fidelity EMT dynamic model of a large-scale PV plant, accomplished through custom model development using the specific-C language in real-time digital simulator hardware (RTDS) and software (RSCAD).

Choi, Jongchan↗

Transient Stability Analysis of Direct Droop-Controlled Grid-Forming Inverter with Current Clipping as Current Limiting Control

This paper investigates the transient stability of the direct droop-controlled grid-forming (GFM) inverter which employs the current clipping-based approach for overcurrent limitation. An equivalent circuit model of the direct-droop GFM inverter with current clipping is developed for this purpose. It is shown that during overcurrent conditions, the GFM inverter with current clipping acts as a voltage source with a virtual resistance behind the inverter filters. To compute the parameters of this virtual resistance an analytical expression is given in the paper. Then utilizing the developed circuit, a criteria to exit current limiting during post-fault conditions is given. The developed analytical approaches are then validated through electromagnetic transient (EMT) simulation results in PSCAD software and finally concluding remarks are drawn.

Mohiuddin, Sheik Mohammad↗

Cryogenic System Preliminary Design for a 0.5m-Long, Conduction-Cooled Nb3Sn Undulator Magnet Prototype

There are several NbTi superconducting undulator (SCU) magnets currently in operation at the Advanced Photon Source (APS) at Argonne National Laboratory (ANL). The development on Nb3Sn-based superconducting undulator magnets at APS is underway due to the potential to further enhance the performance of the SCUs. Superconducting undulator magnets need to keep temperature gradients minimized in order to retain thermal and operating current margin. We have designed the thermal links for efficient heat conduction using 3D finite element analysis (FEA) simulation in COMSOL Multiphysics software, which was later used for the calculation of the temperature distribution across a 0.5 m long, conduction-cooled, Nb3Sn undulator magnet prototype that includes both conductive heat transfer and radiative heating components. We have modelled the evolution of the thermal properties of the magnet winding as well as other cold parts during cool-down from ambient temperature with the operation of a SHI RDK-415D cryocooler to examine the estimated time that is needed for the cooldown as well as the baseline temperature we could achieve. A key result was that a maximum coil delta T = 0.11 K along the designed thermal links and a temperature range of 3.42 K-3.53 K for the winding were predicted at steady state. A pair of G10 support rods for carrying the magnet as well as a pair of current leads made of metals were also designed and optimized for the testing system, targeting for an operation temperature of 4 K and a coil current of 950 A DC.

Zhang, Danlu↗

A Hybrid DC Fault Primary Protection Algorithm for Multi-Terminal HVdc Systems

Protection against dc faults is one of the main technical hurdles faced when operating converter-based HVdc systems. Protection becomes even more challenging for multi-terminal dc (MTdc) systems with more than two terminals/converter stations. In this paper, a hybrid primary fault detection algorithm for MTdc systems is proposed to detect a broad range of failures. Sensor measurements, i.e., line currents and dc reactor voltages measured at local terminals, are first processed by a top-level context clustering algorithm. For each cluster, the best fault detector is selected among a detector pool according to a rule resulting from a learning algorithm. The detector pool consists of several existing detection algorithms, each performing differently across fault scenarios. The proposed hybrid primary detection algorithm: i) offers superior performance compared to an individual detector through a data-driven approach; ii) detects all major fault types including pole-to-pole (P2P), pole-to-ground (P2G), and external dc faults; iii) identifies faults with various fault locations and impedances; iv) is more robust to noisy sensor measurements compared to existing methods; v) does not require exhaustive simulation and sampling for training the model. Performance and effectiveness of the proposed algorithm are evaluated and verified based on time-domain simulations in the PSCAD/EMTDC software environment. The results confirm satisfactory operation, accuracy, and detection speed of the proposed algorithm under various fault scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Contributing to Sunny open source code

The Sunny package is an existing open source software to support the simulation of magnetic spin systems. It is available online under the MIT license here: https://github.com/SunnySuite/Sunny.jl The package aims to include the following features: - Analysis for symmetry-allowed interactions - Monte Carlo algorithms for simulating equilibrium configurations. - Schemes for integrating spin dynamics. - Inference of model Hamiltonians - Support for generalized SU(N) spins - Tools for interpreting experimental data, such as diffraction data, magnetization curves, and heat capacity data

Barros, Kipton↗

Generic Multi-Layer Perceptron Inference Accelerator on FPGA (vneuron) v1.0

We have designed and implemented a neural network inference compute engine (vneuron) that can be deployed in the fabric of any FPGA without using special hardware accelerator primitive. The "vneuron" is purely written in verilog, and supports scalable neural network structure with fully connected layers and ReLU activation ( Multi-Layer Perceptron architecture) with 16 bits of precision. We have demonstrated it on an Xilinx Artix 7 FPGA for a 16-input, 8-output MLP with 3 layer, 1600 parameters. It takes 40 DSP48E and 40 BRAM18, and takes 131 clock cycles for computing (1048 ns when clocked at 125MHz). We include PyTorch quantization from a given floating point model, and provide behavioral verification simulation in the disclosed software package.

Du, Qiang↗

2-D Surface Temperature Simulation Data and Matlab Scripts

SAND2023-07249O The 2-D Surface Temperature Simulation Data and Matlab software can estimate 2D temperature fields from electrical measurements along the edge of the 2D domain. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Sjoberg, Carl Magnus↗

Enabling AI in synthetic biology through Construction File specification

The Construction File (CF) specification establishes a standardized interface for molecular biology operations, laying a foundation for automation and enhanced efficiency in experiment design. It is implemented across three distinct software projects: PyDNA_CF_Simulator, a Python project featuring a ChatGPT plugin for interactive parsing and simulating experiments; ConstructionFileSimulator, a field-tested Java project that showcases 'Experiment' objects expressed as flat files; and C6-Tools, a JavaScript project integrated with Google Sheets via Apps Script, providing a user-friendly interface for authoring and simulation of CF. The CF specification not only standardizes and modularizes molecular biology operations but also promotes collaboration, automation, and reuse, significantly reducing potential errors. The potential integration of CF with artificial intelligence, particularly GPT-4, suggests innovative automation strategies for synthetic biology. While challenges such as token limits, data storage, and biosecurity remain, proposed solutions promise a way forward in harnessing AI for experiment design. This shift from human-driven design to AI-assisted workflows, steered by high-level objectives, charts a potential future path in synthetic biology, envisioning an environment where complexities are managed more effectively.

59 BASIC BIOLOGICAL SCIENCES↗