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At least 1,459 records · Page 81

Image-Based Fracture Surface Defect Characterization Methods for Additively Manufactured Ti-6Al-4V Tested in Fatigue

Abstract Fatigue initiation in additively manufactured samples/parts often occurs at processed-induced defects such as lack-of-fusion (LoF), keyhole, or other morphological/microstructural defects that have unique characteristics and measurable qualities. Attempts at identifying and minimizing such defects have utilized optimized processing conditions along with in situ and ex situ characterization that includes metallography and/or X-ray computed tomography (XCT). This paper highlights the benefits of using fracture surface analyses to detect and quantify defects that may not be detected by metallography/XCT due to sectioning and resolution limits. In addition to using manual quantification of fatigue initiating LoF and keyhole defects on fracture surfaces, image-based machine learning using convolutional neural networks such as U-Net were also used to automate the process. Statistical analyses were used to identify the extreme cases of defects that initiated and accelerated fatigue and to model the distribution of defect size and shape characteristics to distinguish the type of defect. Initial results show agreement between trained machine learning models and ground truth data in defect segmentation, and the distributions of defect characteristics are distinguishable to particular process-induced defect types.

Materials Science↗

Predicting System Response at Unmeasured Locations

Traditional techniques to derive dynamic specification for components have a great deal of uncertainty. One of the major sources of uncertainty is that the number of response measurements in the operational system environment is insufficient to determine the component motion. This inadequacy is due to logistical limitations for data recording in field testing and space limitations for accelerometers, strain gages and associated wiring. Available measurements are often some distance from the component and therefore do not represent component motion. Typical straight-line envelopes of these unrepresentative measurements guarantee an increase in the uncertainty. In this paper multiple methods are attempted to expand a sparse set of field test measurements on a system to responses of interest that cannot be measured in the field due to the limitations. Proof of concept is demonstrated on the Modal Analysis Test Vehicle (MATV). The responses of interest, known as “truth responses”, are measured in a system vibration environment along with an optimized sparse set of 30 field responses. Methods to expand the field responses to the truth responses are demonstrated by comparing the acceleration spectral density of the expanded response to the measured response. Two methods utilize a validated finite element model of the MATV. One is developed from purely experiment based frequency response functions of a laboratory pre-test. Finally, these approaches are designed to drastically reduce the uncertainty of the component in-service motion as a basis for developing specifications that are guaranteed to be conservative with a known (instead of unknown) conservatism.

42 ENGINEERING↗

The Second-phase Development of the China JinPing Underground Laboratory

During 2013-2015 an expansion of the China JinPing underground Laboratory (CJPL) will be undertaken along a main branch of a bypass tunnel in the JinPing tunnel complex. This second phase of CJPL will increase laboratory space to approximately 96,000 m 3 , which can be compared to the existing CJPL-I volume of ∼ 4,000 m 3 . One design configuration has eight additional hall spaces, each over 60 m long and approximately12 m in width, with overburdens of about 2.4 km of rock, oriented parallel to and away from the main water transport and auto traffic tunnels. There are additional possibilities for further expansions at a nearby second bypass tunnel and along the entrance and exit branches of both bypass tunnels, potentially leading to an expanded CJPL comparable in size to Gran Sasso. Concurrent with the excavation activities, planning is underway for dark matter and other rare- event detectors, as well as for geophysics/engineering and other coupled multi-disciplinary sensors. In the town meeting on 8 September, 2013 at Asilomar, CA, associated with the 13 th International Conference on Topics in Astroparticle and Underground Physics (TAUP), presentations and panel discussions addressed plans for one-ton expansions of the current CJPL germanium detector array of the China Darkmatter EXperiment (CDEX) collaboration and of the duel-phase xenon detector of the Panda-X collaboration, as well as possible new detector initiatives for dark matter studies, low-energy solar neutrino detection, neutrinoless double beta searches, and geoneutrinos. JinPing was also discussed as a site for a low-energy nuclear astrophysics accelerator. Geophysics/engineering opportunities include acoustic and micro-seismic monitoring of rock bursts during and after excavation, coupled-process in situ measurements, local, regional, and global monitoring of seismically induced radon emission, and electromagnetic signals. Additional ideas and projects will likely be developed in the next few years, driven by China’s domestic needs and by international experiments requiring access to very great depths.

58 GEOSCIENCES↗

Traffic Control via Connected and Automated Vehicles (CAVs): An Open-Road Field Experiment with 100 CAVs

The CIRCLES project aims to reduce instabilities in traffic flow, which are naturally occurring phenomena due to human driving behavior. Also called “phantom jams” or “stop-and-go waves,” these instabilities are a significant source of wasted energy. Toward this goal, the CIRCLES project designed a control system, referred to as the MegaController by the CIRCLES team, that could be deployed in real traffic. Our field experiment, the MegaVanderTest (MVT), leveraged a heterogeneous fleet of 100 longitudinally controlled vehicles as Lagrangian traffic actuators, each of which ran a controller with the architecture described in this article. The MegaController is a hierarchical control architecture that consists of two main layers. The upper layer is called the Speed Planner and is a centralized optimal control algorithm. It assigns speed targets to the vehicles, conveyed through the LTE cellular network. The lower layer is a control layer, running on each vehicle. It performs local actuation by overriding the stock adaptive cruise controller, using the stock onboard sensors. The Speed Planner ingests live data feeds provided by third parties as well as data from our own control vehicles and uses both to perform the speed assignment. The architecture of the Speed Planner allows for the modular use of standard control techniques, such as optimal control, model predictive control (MPC), kernel methods, and others. The architecture of the local controller allows for the flexible implementation of local controllers. Corresponding techniques include deep reinforcement learning (RL), MPC, and explicit controllers. Depending on the vehicle architecture, all onboard sensing data can be accessed by the local controllers or only some. Likewise, control inputs vary across different automakers, with inputs ranging from torque or acceleration requests for some cars to electronic selection of adaptive cruise control (ACC) setpoints in others. The proposed architecture technically allows for the combination of all possible settings proposed previously, that is {Speed Planner algorithms} × {local Vehicle Controller algorithms} × {full or partial sensing} × {torque or speed control}. As a result, most configurations were tested throughout the ramp up to the MegaVandertest (MVT).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Thermal and Structural Issues of Target Injection into a Laser-Driven Inertial Fusion Energy Chamber

Inertial fusion energy (IFE) targets injected into fusion chambers must withstand the demanding acceleration forces and the intense thermal environment of the fusion chamber. For indirect targets, the ultrathin capsule support membrane is the target component that is most sensitive to acceleration forces. Maintaining the deuterium-tritium (DT) temperature, to prevent a significant increase in DT vapor pressure, is the most critical thermal requirement. Secondarily, material selection of the high-temperature laser entrance hole window is required. Finally, this paper briefly describes how these requirements are satisfied for a laser-driven IFE plant design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Passive Wireless Sensors for Realtime Temperature and Corrosion Monitoring of Coal Boiler Components Under Flexible Operation (Final Technical Report)

Researchers at West Virginia University (WVU) propose to demonstrate inexpensive wireless, high-temperature sensors for real-time monitoring of the temperature and corrosion of metal components, which are commonly used in coal-fired boilers. This study presents the development of cost-effective wireless high-temperature sensors for real-time temperature and corrosion monitoring in coal-fired boilers' metal components. The focus is on fabricating and evaluating chipless radio-frequency identification (RFID) sensors capable of operating between 25-1300 ºC. Efforts were directed towards designing passive RFID sensor and interrogator antenna with a broad frequency range, optimizing a microstrip patch antenna sensor integrated into a "peel-and-stick" format for efficient application to various metal specimens without altering their geometry. Additionally, this research aimed to assess the sensor responses under accelerated high-temperature conditions, correlating corrosion and cracking mechanisms with sensor data. An investigation of through-wall data acquisition techniques was also planned, facilitating unobtrusive monitoring of sensor responses housed within metal enclosures. Ultimately, this work sought to establish a robust passive wireless sensor system for the continuous health monitoring of metal components in operational settings, thereby contributing to enhanced safety and efficiency in coal-fired power plants.

20 FOSSIL-FUELED POWER PLANTS↗

Southeast Regional CO 2 Utilization and Storage Acceleration Partnership (SECARB-USA): Data Management Plan

The “Southeast Regional CO 2 Utilization and Storage Acceleration Partnership” (SECARB-USA) is designed to assess the region’s subsurface resources and burgeoning technology applications. This work supports the U.S. Department of Energy’s (DOE) Office of Fossil Energy’s (FE) mission to help the United States meet its need for secure, affordable, and environmentally sound fossil energy supplies by utilizing the advancements made by the current RCSP initiative to continue to identify and address knowledge gaps.

42 ENGINEERING↗

Practical method and device for enhancing pulse contrast ratio for lasers and electron accelerators

An apparatus and method for enhancing pulse contrast ratios for drive lasers and electron accelerators. The invention comprises a mechanical dual-shutter system wherein the shutters are placed sequentially in series in a laser beam path. Each shutter of the dual shutter system has an individually operated trigger for opening and closing the shutter. As the triggers are operated individually, the delay between opening and closing first shutter and opening and closing the second shutter is variable providing for variable differential time windows and enhancement of pulse contrast ratio.

42 ENGINEERING↗

Method for enhanced additive manufacturing

Systems and methods are disclosed for manufacturing a three dimensional (3D) part. In one implementation a system in accordance with the present disclosure may make use of an additive manufacturing (AM) subsystem for performing an AM operation to form the 3D part. The 3D part may be formed using a plurality of distinct material layers layered one on top of another. The system may also involve at least one of a laser peening (LP) subsystem and a High Velocity Laser Accelerated Deposition (HVLAD) subsystem. The LP subsystem may be used for laser peening a selected subquantity of the layers, to impart improved hardness to the selected subquantity of the layers and/or to the overall 3D part. The HVLAD subsystem may be used to bond at least one of the material layers to a previously laid down one of the material layers.

42 ENGINEERING↗

ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost

Deep learning is revolutionizing many areas of science and technology, especially image, text, and speech recognition. In this paper, we demonstrate how a deep neural network (NN) trained on quantum mechanical (QM) DFT calculations can learn an accurate and transferable potential for organic molecules. We introduce ANAKIN-ME (Accurate NeurAl networK engINe for Molecular Energies) or ANI for short. ANI is a new method designed with the intent of developing transferable neural network potentials that utilize a highly-modified version of the Behler and Parrinello symmetry functions to build single-atom atomic environment vectors (AEV) as a molecular representation. AEVs provide the ability to train neural networks to data that spans both configurational and conformational space, a feat not previously accomplished on this scale. We utilized ANI to build a potential called ANI-1, which was trained on a subset of the GDB databases with up to 8 heavy atoms in order to predict total energies for organic molecules containing four atom types: H, C, N, and O. To obtain an accelerated but physically relevant sampling of molecular potential surfaces, we also proposed a Normal Mode Sampling (NMS) method for generating molecular conformations. Through a series of case studies, we show that ANI-1 is chemically accurate compared to reference DFT calculations on much larger molecular systems (up to 54 atoms) than those included in the training data set.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High Penetration of Photovoltaic Generation Study – Flagstaff Community Power (Final Technical Report, Results of Phases 2-5)

APS’s renewable energy portfolio, driven in part by Arizona’s Renewable Energy Standard (RES) currently includes more than 1100 MW of installed capacity, equating to roughly 3000 GWh of annual production. Overall renewable production is expected to grow to 6000 GWh by 2025. It is expected that distributed photovoltaics, driven primarily by lower cost, will contribute to much of this growth and that by 2025, distributed installations will account for half of all renewable production (3000GHW). As solar penetration increases, additional analysis may be required for routine utility processes to ensure continued safe and reliable operation of the electric distribution network. Such processes include residential or commercial interconnection requests and load shifting during normal feeder operations. Circuits with existing high solar penetration will also have to be studied and results will need to be evaluated for adherence to utility practices or strategy. Increased distributed PV penetration may offer benefits such as load offsetting, but it also has the potential to adversely impact distribution system operation. These effects may be exacerbated by the rapid variability of PV production. Detailed effects of these phenomena in distributed PV applications continue to be studied. Comprehensive, high-resolution electrical models of the distribution system were developed to analyze the impacts of PV on distribution circuit protection systems (including coordination and anti-islanding), predict voltage regulation and phase balance issues, and develop volt/VAr control schemes. Modeling methods were refined by validating against field measurements. To augment the field measurements, methods were developed to synthesize high resolution load and PV generation data to facilitate quasi-static time series simulations. The models were then extended to explore boundary conditions for PV hosting capability of the feeder and to simulate common utility practices such as feeder reconfiguration. The modeling and analysis methodology was implemented using open source tools and a process was developed to aid utility engineers in future interconnection requests. Methods to increase PV hosting capacity were also explored during the course of the study. A 700kVA grid-supportive inverter was deployed on the feeder and each grid support mode was demonstrated. Energy storage was explored through simulation and models were developed to calculate the optimum size and placement needed to increase PV hosting capacity. A tool was developed to aid planners in assigning relative costs and benefits to various strategies for increasing PV hosting capacity beyond current levels. Following the completion of the project, APS intends to use the tools and methods to improve the framework of future PV integration on its system. The tools and methods are also expected to aid other utilities to accelerate distributed PV deployment.

14 SOLAR ENERGY↗

Non-linear Wire Rope Isolator Model to Enhance Transportation Simulation of Fragile Equipment

Abstract Introduction Wire rope isolators are often used as means of vibration isolation for the transportation of fragile machine equipment. When deployed as suspension systems in a transportation scenario, a simple spring–damper model is often used to predict the dynamic loads that act on the structure being transported. However, this simple model has proved to be too simplistic to be used in the development of an accurate numerical model that can predict the vibration levels experienced by the inner components of fragile equipment during its transportation. This paper describes the experimental tests conducted on a wire rope isolator used for the transportation of the prototype SSR1 cryomodule. Materials and methods A hysteretic Bouc–Wen model has been used to analytically describe the force–deformation relationship of the wire rope isolators. The developed model of the isolator has been implemented in a larger model to simulate the actual transportation of the prototype SSR1 cryomodule, a section of the new PIP-II linear accelerator under construction at Fermilab. A series of multibody dynamic simulations with rigid and flexible components was used to numerically determine the acceleration of some critical components. Results and conclusions An actual experimental transportation was simulated using two numerical models: the developed Bouc–Wen model and a conventional spring–damper model. It is shown how the Bouc–Wen formulation of the isolator characteristics drastically improves the correspondence between experimental and simulated results if compared to a spring–damper model, especially in the range of 0–30 Hz which is the most critical for transportation problems.

42 ENGINEERING↗

Metabolic Modification of Sphingobium lignivorans SYK-6 for Lignin Valorization Through the Discovery of an Unusual Transcriptional Repressor of Lignin-Derived Dimer Catabolism

Sphingobium lignivorans SYK-6 catabolizes guaiacylglycerol-..beta..-guaiacyl ether (GGE, a ..beta..-O-4-type dimer) and 1,2-diguaiacylpropane-1,3-diol (DGPD, a ..beta..-1-type dimer) derived from lignin. Recently, SLG_35860 containing TetR- and MarR-type transcriptional regulator motifs was suggested to be involved in the regulation of GGE and DGPD catabolism. Here we investigated the role of SLG_35860 in the transcriptional regulation of GGE and DGPD catabolism genes. SLG_35860 designated ligS repressed 11 genes involved in GGE and DGPD catabolism. LigS binds directly to specific sequences in the promoter region of each gene. The MarR domain was shown to be involved in these bindings; however, GGE, DGPD, and their metabolites did not function as effectors of LigS. We discovered unidentified compound(s) in the black liquor of oxygen-soda anthraquinone pulping of Japanese cedar that SYK-6 cannot metabolize and that acted as effector(s). Therefore, LigS constantly represses the transcription of the GGE and DGPD catabolism genes to low levels. Based on these findings, we examined the productivity of a polymer building block, 2-pyrone-4,6-dicarboxylic acid (PDC), from GGE, DGPD, and a GGE metabolite using an engineered ligS mutant. The rates of PDC production from each compound by this strain were 1.5-6.0 times higher than those of a PDC-producing strain carrying ligS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Review of pulsed power-driven high energy density physics research on Z at Sandia

Pulsed power accelerators compress electrical energy in space and time to provide versatile experimental platforms for high energy density and inertial confinement fusion science. The 80-TW “Z” pulsed power facility at Sandia National Laboratories is the largest pulsed power device in the world today. Z discharges up to 22 MJ of energy stored in its capacitor banks into a current pulse that rises in 100 ns and peaks at a current as high as 30 MA in low-inductance cylindrical targets. Considerable progress has been made over the past 15 years in the use of pulsed power as a precision scientific tool. This paper reviews developments at Sandia in inertial confinement fusion, dynamic materials science, x-ray radiation science, and pulsed power engineering, with an emphasis on progress since a previous review of research on Z in Physics of Plasmas in 2005.

Sinars, D. B. (ORCID:0000000155473532)↗

Neutron-Resonance Transmission Analysis with a Compact Deuterium-Tritium Neutron Generator

Neutron Resonance Transmission Analysis (NRTA) is a spectroscopic technique which uses the resonant absorption of neutrons in the epithermal range to infer the isotopic composition of an object. This spectroscopic technique has relevance in many traditional fields of science and nuclear security. NRTA in the past made use of large, expensive accelerator facilities to achieve precise neutron beams, significantly limiting its applicability. Here, we describe a series of NRTA experiments where we use a compact, low-cost deuterium-tritium (DT) neutron generator to produce short neutron beams (2.6 m) along with a 6 Li-glass neutron detector. The time-of-flight spectral data from five elements – silver, cadmium, tungsten, indium, and 238 U – clearly show the corresponding absorption lines in the 1-30 eV range. The experiments show the applicability of NRTA in this simplified configuration, and prove the feasibility of this compact and low-cost approach. This could significantly broaden the applicability of NRTA, and make it practical and applicable in many fields, such as material science, nuclear engineering, and arms control.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Robustness of Asymptotic Optimal Accelerated Test Plans to Small-Sample Settings

Accelerated testing is a form of testing commonly employed in industry, especially at Sandia National Laboratories, in order to extract information about product lifetime behavior that cannot be acquired under normal operating conditions due to the extensive durations of the intended life- times. As of the writing of this report, there is no known guideline for the design of accelerated tests at the laboratories and yet there is an entire field in the statistical literature on the optimal design of accelerated tests covering a wide range of limitations and constraints available for reference. A potential roadblock to incorporating this knowledge is the common difficulty at Sandia of having severely limited data available for such testing. Nearly all of the methodology presented in the statistical literature is based on asymptotic or large-sample theory and so may not be appropriate for the testing conditions present at Sandia. This report investigates optimal accelerated test plans derived based on small-sample or exact methodology for both a basic test setting as well as a more realistic setting and compares the resulting test plans to those derived based on the large- sample methodology from the literature. It is shown that the large-sample test plans are actually quite robust to the presence of limited data and are generally more flexible than the small-sample test plans.

36 MATERIALS SCIENCE↗

Large scale centrifuge test of a geomembrane-lined landfill subject to waste settlement and seismic loading

Highlights: • A large centrifuge model of a geomembrane-lined landfill was seismically loaded. • The scaled peak acceleration of the strongest input motion was 0.6 g. • Laboratory testing was conducted to obtain properties of the model materials. • Collected data included liner strains due to downdrag and seismic loading. • Results show that settlement and seismic loading can potentially damage geomembranes. • Results can be used to validate numerical models for geomembrane performance. •The laboratory and centrifuge testing data is publicly available. - Abstract: A large scale centrifuge test of a geomembrane-lined landfill subject to waste settlement and seismic loading was conducted to help validate a numerical model for performance based design of geomembrane liner systems. The test was conducted using the 240 g-ton centrifuge at the University of California at Davis under the U.S. National Science Foundation Network for Earthquake Engineering Simulation Research (NEESR) program. A 0.05 mm thin film membrane was used to model the liner. The waste was modeled using a peat-sand mixture. The side slope membrane was underlain by lubricated low density polyethylene to maximize the difference between the interface shear strength on the top and bottom of the geomembrane and the induced tension in it. Instrumentation included thin film strain gages to monitor geomembrane strains and accelerometers to monitor seismic excitation. The model was subjected to an input design motion intended to simulate strong ground motion from the 1994 Hyogo-ken Nanbu earthquake. Results indicate that downdrag waste settlement and seismic loading together, and possibly each phenomenon individually, can induce potentially damaging tensile strains in geomembrane liners. The data collected from this test is publically available and can be used to validate numerical models for the performance of geomembrane liner systems.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

hIPPYlib-MUQ: A Bayesian Inference Software Framework for Integration of Data with Complex Predictive Models under Uncertainty

Bayesian inference provides a systematic framework for integration of data with mathematical models to quantify the uncertainty in the solution of the inverse problem. However, the solution of Bayesian inverse problems governed by complex forward models described by partial differential equations (PDEs) remains prohibitive with black-box Markov chain Monte Carlo (MCMC) methods. We present hIPPYlib-MUQ, an extensible and scalable software framework that contains implementations of state-of-the art algorithms aimed to overcome the challenges of high-dimensional, PDE-constrained Bayesian inverse problems. These algorithms accelerate MCMC sampling by exploiting the geometry and intrinsic low-dimensionality of parameter space via derivative information and low rank approximation. The software integrates two complementary open-source software packages, hIPPYlib and MUQ. hIPPYlib solves PDE-constrained inverse problems using automatically-generated adjoint-based derivatives, but it lacks full Bayesian capabilities. MUQ provides a spectrum of powerful Bayesian inversion models and algorithms, but expects forward models to come equipped with gradients and Hessians to permit large-scale solution. By combining these two complementary libraries, we created a robust, scalable, and efficient software framework that realizes the benefits of each and allows us to tackle complex large-scale Bayesian inverse problems across a broad spectrum of scientific and engineering disciplines. To illustrate the capabilities of hIPPYlib-MUQ, we present a comparison of a number of MCMC methods available in the integrated software on several high-dimensional Bayesian inverse problems. These include problems characterized by both linear and nonlinear PDEs, various noise models, and different parameter dimensions. The results demonstrate that large (~ 50×) speedups over conventional black box and gradient-based MCMC algorithms can be obtained by exploiting Hessian information (from the log-posterior), underscoring the power of the integrated hIPPYlib-MUQ framework.

97 MATHEMATICS AND COMPUTING↗