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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Voltron Compatible Whole Building Root-Fault Detection and Diagnosis

Buildings consume more than 40% of primary energy in the U.S. Malfunctioning sensors, components, and control systems, as well as degrading components in Heating, Ventilating and Air-conditioning (HVAC) and lighting systems are main reasons for energy waste and unsatisfactory indoor environment. Field studies have shown that an energy saving of 5-30% of total building energy consumption and improved indoor air quality can be achieved by simply applying automated fault detection and diagnosis (AFDD), followed by corrections even if these are not done in real time. Extensive research has been made on the development of component level AFDD tools in the past two decades. However, in recent years, the development of method for a whole building level AFDD has received much attention. Here, a whole building fault refers to a fault happening in one subsystem but impact on more than one subsystems, or has a significant impact on building performances, such as building’s energy consumption. Existing component level AFDD tools could fail to detect or give false alarm for faults that trigger abnormalities in multiple subsystems. Isolating such whole building faults, which have impacts on multiple subsystems, is also challenging by simply using component based AFDD solutions. On the other hand, it might be more cost-effective for medium- or small-sized commercial buildings that have subsystems (e.g. primary cooling subsystem, air loop subsystem, heating subsystem, lighting subsystem, etc.) to install one whole building level AFDD tool, rather than many component level AFDD tools, to focus on significant faults. The focus of this project is firstly to provide training opportunities in building AFDD research area for undergraduate students and to develop a workforce pipeline in building sciences. The objective of the proposed research activities is to develop cost-effective and scalable AFDD solutions for whole building level faults. The developed AFDD solution is VOLTTRONTM compatible to further increase its plug-n-play capacity and the market penetration. VOLTTRONTM is an open-source innovative distributed control and sensing software platform developed by the Pacific Northwest National Laboratory. A VOLTTRONTM compatible AFDD tool brings the benefits such as low-cost deployment, and better building to grid integration, etc. The performance of the developed whole building AFDD tools is evaluated using data collected from a mixed-use medium-sized university campus building. Another significant goal of this project is to engage undergraduate students in research activities and expose them to building control and AFDD fields. A demonstration building – Nesbitt Hall at Drexel University is identified for this study. This demonstration building has a typical HVAC system configuration, which includes a water-cooled chiller system, three variable air volume (VAV) air handling unit (AHU) systems, and a hydronic heating system. Faults, that are expected to have a whole building level impact, are artificially implemented in this demonstration building for three different seasons. Building data have been collected in this project, which include fault free building automation system (BAS) data and BAS data that contain system behaviors caused by artificially implemented and naturally occurred faults. These collected data are used to evaluate the developed whole building AFDD tools. A data-driven method, which includes a weather and schedule-based pattern matching (WPM) method and Feature based Principal Component Analysis (FPCA) method, is developed for whole building level fault detection. Parameter sensitivity tests, including snapshot window size, data sample searching pool size, etc., are implemented to evaluate the impacts of various WPM-FPCA parameters. A data-driven and expert knowledge/rule-based method using Bayesian Network (BN) and WPM is developed for whole building level fault diagnosis. The developed WPM-BN method, which includes a two-layer BN structure model and BN parameters, are either learned from baseline data or developed from expert knowledge. The developed whole building AFDD tools are evaluated using BAS data collected from the demonstration building. Using the evaluation data set, the WPM-FPCA fault detection method is evaluated under two different Principle Component (PC) retention rates, i.e., 0.65 retention rate and 0.95 retention rate. It is observed that when using 0.65 PC retention rate, the WPM-FPCA fault detection method achieves a 79% fault detection rate (this rate reaches to 85% when including the six make-up fault test cases discussed in the next bullet), while when using 0.95 PC retention rate, the WPM-FPCA fault detection method achieves 100% fault detection rate (this rate remains to be 100% when including the six make-up fault test cases). Under both PC retention rates, the WPM-FPCA fault detection method demonstrates 0% false alarm rates. Using the evaluation data set, the developed WPM-BN fault diagnosis method has successfully diagnosed thirteen (13) faults out of the fourteen (14) fault test cases. The one mis-diagnosed case exhibits fewer fault symptoms in different subsystems, when compared with other fault test cases. Overall speaking, the developed whole building AFDD solutions demonstrate satisfactory fault detection/diagnosis accuracy with very low false alarm rate. Lastly, a survey and market study has been performed to understand the existing AFDD market, including its gaps and needs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

High fidelity simulation and analysis of liquid jet atomization in a gaseous crossflow at intermediate Weber numbers

Recent advances in numerical methods coupled with the substantial enhancements in computing power and the advent of high performance computing have presented first principle, high fidelity simulation as a viable tool in the prediction and analysis of spray atomization processes. The credibility and potential impact of such simulations, however, has been hampered by the relative absence of detailed validation against experimental evidence. The numerical stability and accuracy challenges arising from the need to simulate the high liquid-gas density ratio across the sharp interfaces encountered in these flows are key reasons for this. In this work we challenge this status quo by presenting a numerical model able to deal with these challenges, employing it in simulations of liquid jet in crossflow atomization and performing extensive validation of its results against a carefully executed experiment with detailed measurements in the atomization region. We then proceed to the detailed analysis of the flow physics. The computational model employs the coupled level set and volume of fluid approach to directly capture the spatiotemporal evolution of the liquid-gas interface and the sharp-interface ghost fluid method to stably handle high liquid-air density ratio. Adaptive mesh refinement and Lagrangian droplet models are shown to be viable options for computational cost reduction. Moreover, high performance computing is leveraged to manage the computational cost. The experiment selected for validation eliminates the impact of inlet liquid and gas turbulence and focuses on the impact of the crossflow aerodynamic forces on the atomization physics. Validation is demonstrated by comparing column surface wavelengths, deformation, breakup locations, column trajectories and droplet sizes, velocities, and mass rates for a range of intermediate Weber numbers. Analysis of the physics is performed in terms of the instability and breakup characteristics and the features of downstream flow recirculation, and vortex shedding. Formation of “Λ” shape windward column waves is observed and explained by the combined upward and lateral surface motion. The existence of Rayleigh-Taylor instability as the primary mechanism for the windward column waves is verified for this case by comparing wavelengths from the simulations to those predicted by linear stability analyses. Physical arguments are employed to postulate that the type of instability manifested may be related to conditions such as the gas Weber number and the inlet turbulence level. The decreased column wavelength with increasing Weber number is found to cause enhanced surface stripping and early depletion of liquid core at higher Weber number. A peculiar “three-streak-two-membrane” liquid structure is identified at the lowest Weber number and explained as the consequence of the symmetric recirculation zones behind the jet column. It is found that the vortical flow downstream of the liquid column resembles a von Karman vortex street and that the coupling between the gas flow and droplet transport is weak for the conditions explored.

42 ENGINEERING↗
DOE OSTI2021

Measuring Gas Transport and Sorption in Large Intact Geologic Specimens via the Piezometric Method

Uptake of noble gases into heterogeneous geologic core samples was measured using a piezometric methodology. In addition to measuring accessible porosity—as with gas pycnometry—by monitoring the rate of pressure decay, this method can also be used to estimate the gas effective diffusivity in the sample. In contrast to previous applications of this method, where milligram quantities of fractured grains are characterized, here approximately kilogram core samples were left intact when tested. In doing so, a more representative sample of the heterogeneous field geology is provided. Additionally, alteration of the pore structure and connectivity during sample preparation is avoided. Furthermore, to scale the piezometric method from milligrams to kilograms, the system was designed to operate at medium vacuum (1 to 100 Pa) to restrict transport in pores less than approximately 60 µm to large Knudsen numbers. To test the system performance, two samples of interest were selected: a rhyolitic welded tuff from Blue Canyon Dome at the Energetic Materials Research and Testing Center and a zeolitized non-welded rhyolitic tuff from the Nevada National Security Site. Three noble gases were utilized in this test series; Argon and xenon as they are of direct interest to nuclear monitoring efforts and helium as it is a weakly adsorbing reference standard. Additionally, mercury intrusion porosimetry measurements were made on subsamples of the core to compare the observed porosity by the two methods and to discuss gas transport rates in the context of the measured pore distribution.

58 GEOSCIENCES↗
DOE OSTI2026

An immersed interface method for microstructure-scale electrochemical battery models: numerical formulation and performance portable implementation

We present the numerical formulation, verification, and performance portable implementation of an immersed interface method for microstructure scale electrochemical modeling of batteries. The innovation in this approach is the resolution of chemical species and electrostatic potential discontinuities at active interfaces without the use of interface conforming unstructured grids. A unified formulation on Cartesian grids for all domains (electrodes and electrolyte) is used with interfacial flux conditions applied using volume fraction or “color” function gradients. We have developed one dimensional and two dimensional test cases with analytic solutions for electrochemical modeling using which we verified the consistency and accuracy of our scheme. Our solver is also validated against solutions from a macroscale model and an unstructured multi-subdomain solver for a full lithium ion cell. We then demonstrated the utility of our solver on an image-based complex battery electrode microstructure at high charging rate. Our technique also exhibits good scalability on distributed memory architectures using central processing units (CPU), with problem sizes up to 1.8 billion degrees of freedom and with 5400 ranks. Initial performance studies of our open-source performance portable solver showed about 70 times speed up using a graphics processing unit (GPU) compared to single compute core for a problem with 4 million cells.

25 ENERGY STORAGE↗
DOE OSTI2026

Seed-Mediated Colloidal Synthesis of Multimetallic and High-Entropy Alloy Nanocrystal Libraries with Enhanced Catalytic Performance

Engineering colloidally stable multimetallic nanocrystals offers many benefits in a wide range of applications and allows manipulation of physical, chemical, and electronic properties of materials at the nanoscale. Synthesis routes are challenged by the chemical complexity required to temporally and spatially coordinate the reduction and alloying of multiple metal species, which has hampered the development of tunable libraries of colloidal materials to date. Here, in this work, we demonstrate a seed-mediated synthesis method to incorporate five or more metal elements into uniform, colloidally stable nanocrystals. By integrating machine learning-accelerated simulations, the synthesis of shortlisted high-entropy alloy nanocrystals was demonstrated. Multiple seed materials can be used, leading to a library of multimetallic nanocrystals with tunable electronic, physical, and alloy structures. The advantage of this synthetic protocol is highlighted in the preparation of catalytic materials that showed 2 orders of magnitude higher reaction rates than monometallic catalysts and outstanding thermal stability, thus highlighting the promise of this approach for high-performance materials in many areas.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

The Transference Number

The performance of rechargeable batteries and other electrochemical systems depends on the rate at which the working ion (often a cation) is transported from one electrode to the other. The cation transference number is an important transport parameter that affects this rate. The purpose of this perspective is to distinguish between approximate and rigorous methods used in the literature to measure the transference number. We emphasize the fact that this parameter is dependent on the reference frame used in the analysis; care must be taken when comparing values obtained from different sources to account for differences in reference frames. We present data obtained from a well‐characterized electrolyte. We compare rigorously determined transference numbers in two reference frames with values obtained by an approximate method. We conclude with a qualitative discussion of the relationship between the transference number and salt concentration gradients that are obtained when current is drawn through a battery.

Gao, Kevin W.↗
DOE OSTI2019

Feasibility of using computed tomography texture analysis parameters as imaging biomarkers for predicting risk grade of gastrointestinal stromal tumors: comparison with visual inspection

Purpose: To evaluate the feasibility of using computed tomography texture analysis (CTTA) parameters for predicting malignant risk grade and mitosis index of gastrointestinal stromal tumors (GISTs), compared with visual inspection. Method and materials: CTTA was performed on portal phase CT images of 145 surgically confirmed GISTs (mean size: 42.9 ± 37.5 mm), using TexRAD software. Mean, standard deviation, entropy, mean of positive pixels (MPP), skewness, and kurtosis of CTTA parameters, on spatial scaling factor (SSF), 2–6 were compared by risk grade, mitosis rate, and the presence or absence of necrosis on visual inspection. CTTA parameters were correlated with risk grade. Diagnostic performance was evaluated with receiver operating characteristic curve analysis. Enhancement pattern, necrosis, heterogeneity, calcification, growth pattern, and mucosal ulceration were subjectively evaluated by two observers. Results: Three to four parameters at different scales were significantly different according to the risk grade, mitosis rate, and the presence or absence of necrosis (p < 0.041). MPP at fine or medium scale (r = − 0.547 to − 393) and kurtosis at coarse scale (r = 0.424–0.454) correlated significantly with risk grade (p < 0.001). HG-GIST was best differentiated from LG-GIST by MPP at SSF 2 (AUC, 0.782), and kurtosis at SSF 4 (AUC, 0.779) (all p < 0.001). CT features predictive of HG-GIST were density lower than or equal to that of the erector spinae muscles on enhanced images (OR 2.1; p = 0.037; AUC, 0.59), necrosis (OR, 6.1; p < 0.001; AUC, 0.70), heterogeneity (OR, 4.3; p < 0.001; AUC, 0.67), and mucosal ulceration (OR, 3.3; p = 0.002; AUC, 0.62). Conclusion: Using TexRAD, MPP and kurtosis are feasible in predicting risk grade and mitosis index of GISTs. CTTA demonstrated meaningful accuracy in preoperative risk stratification of GISTs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Transcatheter arterial infusion for pancreatic cancer: a 10-year National Cancer Center experience in 115 patients and literature review

Purpose: To evaluate the efficacy and safety of transcatheter arterial infusion (TAI) for the treatment of pancreatic cancer in patients ineligible for or refractory to systemic chemotherapy. Materials and methods: The medical records of 115 consecutive patients (mean age, 58.9 years; 71 males) with documented pancreatic cancer ineligible for or refractory to systemic chemotherapy and underwent TAI between February 2007 and January 2017 were reviewed. Results: A total of 224 TAI sessions [mean, 1.9 (range 1–8)] were performed. Technical success rate was 100%. Disease control (i.e., complete response, partial response, and stable disease) was achieved in 72 (62.6%) patients. The median progression-free survival and median overall survival were 56 days and 147 days, respectively. Subgroup analysis revealed that disease control, progression-free survival, and overall survival were significantly improved in patients with an Eastern Cooperative Oncology Group score of ≤ 1 compared with those in patients with an Eastern Cooperative Oncology Group score of 2 (all p < 0.001) and in patients who received > 1 sessions of TAI compared with that in patients who received only 1 session of TAI (p = 0.012, < 0.001, and = 0.002, respectively). A major complication in the form of cerebral infarction occurred in 1 (0.9%) patient 1 day after the procedure. This patient was treated with conservative therapy and recovered without permanent adverse sequelae. No other major complications were observed. Conclusions: TAI may be effective and safe for the treatment of pancreatic cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

A fully-implicit high-order system thermal-hydraulics model for advanced non-LWR safety analyses

An advanced system analysis tool is being developed for advanced reactor safety analysis. This paper describes the underlying physics and numerical models used in the code, including the governing equations, the stabilization schemes, the high-order spatial and temporal discretization schemes, and the Jacobian Free Newton Krylov solution method. The effects of the spatial and temporal discretization schemes are investigated. Additionally, a series of verification test problems are presented to confirm the high-order schemes. Furthermore, it is demonstrated that the developed system thermal-hydraulics model can be strictly verified with the theoretical convergence rates, and that it performs very well for a wide range of flow problems with high accuracy, efficiency, and minimal numerical diffusions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Delayed gamma-ray spectroscopy with lanthanum bromide detector for non-destructive assay of nuclear material

High-energy delayed γ-ray spectroscopy is a potential technique for directly assaying spent fuel assemblies and achieving the safeguards goal of quantifying nuclear material inventories for spent fuel handling, interim storage, reprocessing facilities, repository sites, and final disposal. Requirements for the γ-ray detection system, up to ~6 MeV, can be summarized as follows: high efficiency at high γ-ray energies, high energy resolution, good linearity between γ-ray energy and output signal amplitude, ability to operate at very high count rates, and ease of use in industrial environments such as nuclear facilities. High Purity Germanium Detectors (HPGe) are the state of the art and provide excellent energy resolution but are limited in their count rate capability. Lanthanum Bromide (LaBr 3 ) scintillation detectors offer significantly higher count rate capabilities at lower energy resolution. Thus, LaBr 3 detectors may be an effective alternative for nuclear spent-fuel applications, where count-rate capability is a requirement. This paper documents the measured performance of a 2” (length) × 2” (diameter) of LaBr3 scintillation detector system, coupled to a negatively biased PMT and a tapered active high voltage divider, with count-rates up to ~3 Mcps. An experimental methodology was developed that uses the average current from the PMT’s anode and a dual source method to characterize the detector system at specific very high count rate values. Delayed γ-ray spectra were acquired with the LaBr 3 detector system at the Idaho Accelerator Center, Idaho State University, where samples of ~3g of 235 U were irradiated with moderated neutrons from a photo-neutron source. Results of the spectroscopy characterization and analysis of the delayed γ-ray spectra acquired indicate the possible use of LaBr3 scintillation detectors when high count rate capability may outweigh the lower energy resolution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Modified Energy Span Analysis of Catalytic Parallel Pathways and Selectivity

Mechanistic modeling provides vital insights into catalytic reactions. To analyze complex reaction networks with parallel pathways, we leverage the graph theory approach of the Energy Span Model (ESM) to develop a modified energy span analysis (MESA). A new method of cycle plots is proposed to perform reaction pathways analysis visually. We demonstrate this method on two published models: one describing carbon monoxide oxidation and the other simulating ethylene conversion to propanal via hydroformylation or ethane via hydrogenation. Fundamental insights explain kinetic observables, such as a reactant’s negative reaction order. General principles are revealed, such as rate-determining surface species being outside the primary reaction flux cycle and pathway selectivity being a purely kinetic property when reaction conditions are not near equilibrium. Lastly, we demonstrate MESA’s consistency with published microkinetic modeling results, highlighting this technique’s extension of the ESM to heterogeneous catalysts using collision theory to describe adsorption steps and concentration effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Atomic Layer Deposition of Cu Electrocatalysts on Gas Diffusion Electrodes for CO 2 Reduction

Electrochemical reduction of CO 2 using Cu catalysts enables the synthesis of C 2+ products including C 2 H 4 and C 2 H 5 OH. Here, in this study, Cu catalysts were fabricated using plasma-enhanced atomic layer deposition (PEALD), achieving conformal deposition of catalysts throughout 3-D gas diffusion electrode (GDE) substrates while maintaining tunable control of Cu nanoparticle size and areal loading. The electrochemical CO 2 reduction at the Cu surface yielded a total Faradaic efficiency (FE) > 75% for C 2+ products. Parasitic hydrogen evolution was minimized to a FE of ~10%, and a selectivity of 42.2% FE for C 2 H 4 was demonstrated. Compared to a line-of-sight physical vapor deposition method, PEALD Cu catalysts show significant suppression of C 1 products compared to C 2+ , which is associated with improved control of catalyst morphology and conformality within the porous GDE substrate. Finally, PEALD Cu catalysts demonstrated a stable performance for 15 h with minimal reduction in the C 2 H 4 production rate.

42 ENGINEERING↗
DOE OSTI2020

Data-driven Cyberattack Detection for Photovoltaic (PV) Systems through Analyzing Micro-PMU Data

With increasing exposure to software-based sensing and control, Photovoltaic (PV) systems are facing higher risks of cyber attacks. Here, to ensure the system stability and minimize potential economic losses, it is imperative to monitor operating states and detect attacks at the early stage. To meet this demand, Micro-Phasor Measurement Units (μPMU) are increasingly popular in monitoring distribution networks. However, due to the relatively low sampling rate, μPMU has not yet been used to detect and classify cyber-attacks in power electronics enabled smart grid. To our knowledge, this is one of the first attempts to use μPMU to detect cyber attacks that degrade the performance of power electronics systems. We propose to apply data-driven methods on micro-PMU data to implement attack detection. We have evaluated data-driven methods, including decision tree (DT), K-nearest neighbor (KNN), support vector machine (SVM), artificial neural network (ANN), long short-term memory (LSTM) and convolutional neural network (CNN). The proposed CNN model achieves the required performances with the highest 99.23% accuracy and 0.9963 F 1 score.

14 SOLAR ENERGY↗
DOE OSTI2019

Challenges in Clinical Trial Implementation: Results from a Survey of the National Accreditation Program of Breast Centers (NAPBC)

Background: Although the results of clinical trials often guide best practices, changing clinical practice based on clinical trial results can be challenging. The objective of this study was to examine provider-reported barriers to adopting best clinical practices according to clinical trial data. Methods: A cross-sectional survey was conducted of providers from the National Accreditation Program for Breast Centers about barriers that prevent the incorporation of trial findings. Descriptive analyses and multivariable analyses were performed to determine provider characteristics that were significantly associated with reported barriers. Results: Overall, 383 institutions participated (63.5% response rate), with a total of 1226 physicians responding to the survey (80% response rate). Providers identified national guidelines and meetings as the most compelling way to receive practice-changing information. They reported the following internal barriers to trial implementation: patient preference (45%), strongly held beliefs by partners/colleagues (37%), and insufficient time to discuss new practices (30%). External barriers preventing trial implementation included a lack of agreement from multidisciplinary tumor boards (32%), fear of reimbursement loss (23%), and resistance from clinical staff (20%). Reported barriers differed by provider specialty, with plastic surgeons and radiation oncologists reporting that strongly held beliefs by partners/colleagues and disagreement from multidisciplinary tumor boards were the most significant factors preventing clinical trial implementation. Conclusions: Physician beliefs and patient preferences are the most frequently reported barriers to clinical trial implementation. Tactics to better educate providers about how to explain new clinical trial data to their patients and colleagues are needed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Magnetic Partitioning Nanofluid for Rare Earth Extraction from Geothermal Fluids

Rare earth metals are critical materials in a wide variety of applications in generating and storing renewable energy and in designing more energy efficient devices. Extracting rare earth metals from geothermal brines is a very challenging problem due to the low concentrations of these elements and engineering challenges with traditional chemical separations methods involving packed sorbent beds or membranes that would impede large volumetric flow rates of geothermal fluids transitioning through the plant. We are demonstrating a simple and highly cost-effective nanofluid-based method for extracting rare earth metals from geothermal brines. Core-shell composite nanoparticles are produced that contain a magnetic iron oxide core surrounded by a shell made of silica or metal-organic framework (MOF) sorbent functionalized with chelating ligands selective for the rare earth elements. By introducing the nanoparticles at low concentration (≈0.05 wt%) into the geothermal brine after it passes through the plant heat exchanger, the brine is exposed to a very high concentration of chelating sites on the nanoparticles without need to pass through a large and costly traditional packed bed or membrane system where pressure drop and parasitic pumping power losses are significant issues. Instead, after a short residence time flowing with the brine, the particles are effectively separated out with an electromagnet and standard extraction methods are then applied to strip the rare earth metals from the nanoparticles, which are then recycled back to the geothermal plant. Recovery efficiency for the rare earths at ppm level has now been measured for both silica and MOF sorbents functionalized with a variety of chelating ligands. A detailed preliminary techno-economic performance analysis of extraction systems using both sorbents showed potential to generate a promising internal rate of return (IRR) up to 20%.

58 GEOSCIENCES↗
DOE OSTI2024

Evaluation of In-Situ AM Process Monitoring Techniques and Potential for Detecting Process Anomalies and Undesirable Microstructures

The US Department of Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing rapid qualification of new materials for fabrication of nuclear relevant components using advanced manufacturing techniques. Particular interest is placed on code-qualifying stainless steel (SS) 316H processed by laser powder bed fusion (LPBF) additive manufacturing. A paradigm that incorporates data from in-situ sensing during the printing, ex-situ characterization, and advanced artificial intelligence–based models was established under the Transformation Challenge Reactor (TCR) program to develop a pedigree for each fabricated component that could be tracked from the feedstock to the component’s release for application. Under the TCR program, the Peregrine software was developed as a tool for incorporating the vast amounts of in-situ and ex-situ characterization data collected; all data stored on a rapidly growing digital platform. The digital platform allows for users to link site-specific process anomalies to the macro- and microstructure. The platform will eventually be able to predict component performance, which will be crucial to qualifying materials and components in risk-averse industries such as those supporting and building nuclear reactors. Current in-situ process monitoring techniques that are already integrated with software like Peregrine are advantageous for identifying process anomalies including powder spatter, component edge swelling, recoating-build interactions, and so on. However, additional data are required to fully predict the resulting microstructures needed for identifying relationships to component performance. The rapid cooling rates observed in LPBF are some of the highest of any bulk manufacturing process, resulting in heterogenous microstructures and typically causing anisotropy in mechanical properties. Moreover, evolved residual thermal stresses are high, which can cause severe defects such as delamination or cracking. Therefore, other in-situ monitoring methods are warranted for exploration to measure and map the thermal history, and potentially the stress state, of each build. This report summarizes different in-situ monitoring strategies proposed for LPBF with a focus on the more developed sensor systems. Novel capabilities for measuring melt pool temperatures are also addressed to better inform modeling efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2021

PlasmidMaker: a Versatile, Automated, and High Throughput End-to-End Platform for Plasmid Construction

Plasmids are used extensively in basic and applied biology. However, design and construction of plasmids, specifically the ones carrying complex genetic information, remains one of the most time-consuming, labor-intensive, and rate-limiting steps in performing sophisticated biological experiments. Here, we report the development of a versatile, robust, automated end-to-end platform named PlasmidMaker that allows error-free construction of plasmids with virtually any sequences in a high-throughput manner. This platform consists of a most versatile DNA assembly method using Pyrococcus furiosus Argonaute ( Pf Ago)-based artificial restriction enzymes, a user-friendly frontend for plasmid design, and a backend that streamlines the workflow and integration with a robotic system. As a proof of concept, we used this platform to generate ~100 plasmids from six different species ranging from 5 to 18 kb in size from up to 11 DNA fragments within 3 days. PlasmidMaker should greatly expand the potential of synthetic biology.

Enghiad, Behnam↗
NASA NTRS1974

Quantizing and sampling considerations in digital phased-locked loops

The quantizer problem is first considered. The conditions under which the uniform white sequence model for the quantizer error is valid are established independent of the sampling rate. An equivalent spectral density is defined for the quantizer error resulting in an effective SNR value. This effective SNR may be used to determine quantized performance from infinitely fine quantized results. Attention is given to sampling rate considerations. Sampling rate characteristics of the digital phase-locked loop (DPLL) structure are investigated for the infinitely fine quantized system. The predicted phase error variance equation is examined as a function of the sampling rate. Simulation results are presented and a method is described which enables the minimum required sampling rate to be determined from the predicted phase error variance equations.

Hurst, G. T.↗