Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data enhancement”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18

Method for enhancing a computer to estimate an uncertainty of an onset of a signal of interest in time-series noisy data

A computer-implemented method of enhancing a computer to estimate an uncertainty of an onset of a signal of interest in time-series noisy data. A first mathematical model of first time series data that contains only noise is calculated. A second mathematical model of second time series data that contains the noise and an onset of a signal of interest in the second time series data is calculated. A difference is evaluated between a first combination, being the first mathematical model and the second mathematical model, and a second combination, being the first time series data and the second time series data, wherein evaluating is performed using a generalized entropy metric. A specific time when an onset of the signal of interest occurs is estimated from the difference. An “a posteriori” distribution is derived for an uncertainty of the specific time at which the onset occurs.

Stracuzzi, David John↗

Transmission of Images on High-Temperature Nuclear-Grade Metallic Pipe with Ultrasonic Elastic Waves

Transmission of information using elastic ultrasonic waves on existing metallic pipes provides an alternative communication option for a nuclear facility. The advantages of this approach consist of transmitting information through barriers, such as the containment building wall, with minimal modification of the existing hardware. Because bit rates on the order of kilobits per second are achievable, relatively large volumes of data, such as images, can be transmitted. A viable candidate for an ultrasonic communication channel is a stainless steel pipe of the chemical volume control system (CVCS) that penetrates through the reactor containment building wall through a sealed tunnel. To study ultrasonic communication under simulated nuclear facility conditions of high temperature, a test article was developed by installing heating tapes, temperature controllers, and thermal insulation on a laboratory CVCS-like stainless steel pipe. High temperature and radiation-resilient lithium niobate ultrasonic transducers were utilized for information transmission on the heated pipe. The amplitude shift keying (ASK) digital communication protocol was developed and implemented in a GNU Radio software-defined radio environment. A root-raised-cosine filter was introduced to suppress ultrasonic transducer ringing and thus reduce inter-symbol interference. This resulted in the enhancement of the data transmission bit rate compared to information encoding with square pulses. Demonstrations of communication at high temperature included transmission of a 90-KB image at the bit rate of 10 Kbps with a bit error rate of 10 -3 across a 6-ft-long straight pipe heated up to 230 degrees C. Additional preliminary studies were conducted to evaluate ultrasonic communication system resilience to environmental degradation and damage.

42 ENGINEERING↗

Robotics for HVAC applications: A critical review and future perspectives

Recent advances in artificial intelligence (AI), enhanced computational capabilities, and innovations in sensors and hardware have driven the increasing development and application of robots in heating, ventilation, and air conditioning (HVAC) systems. We selected and reviewed 101 studies published between 2005 and 2025, sourced from IEEE Xplore, Scopus, Web of Science, and the ACM Digital Library. To analyze these works, we developed a five-dimensional analytical framework (morphology, sensing, navigation, task execution, and system integration), inspired by the Springer Handbook of Robotics and tailored specifically for robotic applications in HVAC. Based on the reviewed studies, six distinct tasks spanning the entire HVAC lifecycle have been identified. Among the six tasks, inspection and maintenance dominate (59 %), followed by indoor monitoring and auditing (21 %), whereas leakage detection, comfort support, and installation/retrofit remain less explored. To address the identified gaps, this review proposes future research directions including investigating robot-aware HVAC design principles, developing multimodal HVAC sensing and data fusion techniques, enhancing robot training and hardware capabilities, and expanding robotic applications beyond Maintenance and Operations (M&O). The findings from this review inform future robotics research for HVAC applications and ultimately enhance system affordability, energy efficiency, resilience or reliability, and occupant environmental comfort. Moreover, it seeks to inspire researchers to explore the intersections of robotics, computer science, building science, and HVAC engineering fostering advancements in this multidisciplinary field.

AI↗

Materials genome innovation for computational software (magics) center

Functional layered material (LM) architectures will dominate nanomaterials science in this century. We have developed theory, modeling, simulation, and software and data tools that enhance understanding and AI guide synthesis, enable characterization of complex structures, and improve capabilities in the predictive design and growth of LMs. Research at the Center has focused on: Computational synthesis and characterization: AI guided synthesis and experimental synthesis of stacked LMs with tailored properties via optimized chemical vapor deposition (CVD) growth and liquid-phase exfoliation; study defects, edges, grain boundaries, wrinkling of atomic layers and their effects on chemical, mechanical, electrical, and optical properties. Far-from-equilibrium processes: Joint experimental and simulation based probe of electronic processes with NAQMD and ultrafast X-ray free-electron laser (XFEL) and ultrafast electron diffraction (UED) facilities at Stanford. Experimentally validate NAQMD by ultrafast electron diffraction and X-ray spectroscopy studies of structural and excited state dynamics, shape fluctuations, and phonon dynamics. Scalable software: Simulation engines for desktop-to-exascale platforms using low-overhead, linear-scaling QMD algorithms; divide-conquer-recombine NAQMD with electronic excitations; extended-Lagrangian reactive molecular dynamics (RMD), machine learning (ML) based neural-network quantum molecular dynamics (NNQMD), and super-state accelerated molecular dynamics (AMD) and kinetic Monte Carlo codes; thermal and electrical transport software; and design 3D architectures of LMs with desired functionality using scalable software. Distribution of software and data, and training: Software and simulation-experimental data generated within the Center are distributed to the materials science community via Berkeley Materials Project (MP) framework. We have also organized three workshops for software distribution and training at USC (Nov. 2017, Mar. 2018) and Gaithersburg, MD (Nov. 2018) to train researchers, with the last one in focused on underrepresented groups, in collaboration with Howard University which is one of the largest HBCUs. The Center supported a total of 46 personnel and 6 undergraduate students. These include 14 faculty, 11 postdoctoral research associates, 20 graduate research assistants, and mentored 6 undergraduate students. This resulted in the publications of 63 research papers that include 46 publications on Reactive and Quantum Dynamics Simulations, 13 publications on Machine Learning for Quantum Materials, and 4 publications on Quantum Computing.

2D Materials↗

Foam Fracturing Fluid Half-life Experimental Data

Foam thermal stability was studies at Temple University in collaboration with Oak Ridge National Lab (ORNL). The goal of this project is to explore thermally stable foams as hydrofracking fluid media for potential applications in enhanced geothermal system (EGS). Data generated from this project will allow researchers to explore foam as potential fracturing fluid. More than 800 data points on the half-life of foams are recorded in Excel files in the included archive resource (Half-life of Foams with Different Surfactants and Stabilizing Agents). The Excel file within each surfactant folder contains half-life data of the respective surfactant with different stabilizing agents, pressure, and temperature. The respective folders also contains Word files describing the details of the data included in the respective Excel sheet.

15 GEOTHERMAL ENERGY↗

Thermodynamic Model and Initial Experimental Investigation of Air Dehumidification through Electrically Charged Vapor Capturing Electrostatic Droplets

The removal of water vapor from the air to reduce relative humidity is a well known indoor environmental comfort requirement. Common dehumidification approaches require a substantial amount of energy and usually involve the cooling of atmospheric humid air below its dew point or the use of absorbent/adsorbent materials to extract water vapor out of the air. More recently, researchers investigated the effect of electrostatic forces for enhancing water vapor condensation with the goal to reduce the energy consumption associated with dehumidification. However, the studies are limited, and there is a lack of correlations that can predict the dehumidification rate. In this thesis, a broad theoretical investigation to study the electrostatically enhanced condensation processes was carried out. These processes consist of the use of highly charged particles, preferably highly charged water droplets to attract polar water vapor molecules to their surfaces and promote condensation, a phenomenon known as dielectrophoresis. The electrical charge promotes the reduction of the vapor pressure on the droplets' surface with respect to the saturated pressure predicted by the Kelvin equation on curved surfaces and, consequently, the equilibrium between evaporation and condensation is shifted towards condensation. This investigation resulted in the development of a thermodynamics model, which was able to predict an effective size range of the charged droplets for optimal dehumidification, under ideal conditions. The range resulted in about 2 to 4 m in diameter, while the electrical charge was kept to the maximum limit predicted by the Rayleigh model. A sensitivity analysis on the variation of the size and the charge of the charged droplets was also performed. In terms of dehumidification rates, when six electrospray heads, i.e. the maximum number of heads tested in the experimental campaign, were considered, the model predicted very limited rates, way lower than the target of this research, i.e. a dehumidification rate in terms of relative humidity of 5 % with an air flow rate of 5 cfm. While ways to increase this rate existed, their implementation proved difficult for this initial investigation. According to the requirements predicted by the model, the use of electrosprays appeared the most suitable solution for the production of small but highly charged droplets. The electrospray features and operational modes were studied in detail and an electrospray assembly was designed to be tested in this initial experimental investigation. For this initial investigation, an experimental system was designed and built to validate the thermodynamics model and with the goal to achieve a dehumidification rate of 5 % in terms of relative humidity with an air flow rate of 5 cfm. The experimental system consisted of a wind tunnel test apparatus, dew point sensors, thermocouples for temperature measurements, pressure sensors and other devices. The experimental system was equipped with a computerized data acquisition and storage system. The system was suitable to evaluate the air water content differential before and after the test section where the electrospray heads were installed. The air water content differential was evaluated in terms of the ∆ω/ω_1 ratio, to eliminate the dependence on the dry bulb temperature along the test apparatus. This work presented initial experimental data for electrostatically enhanced dehumidification processes. Working parameters, such as air and water flow rates, high voltage potentials and polarity, deionized water types with different electrical conductivity, were varied to find the best combination for an improved dehumidification. With the set up used and the conditions considered, it was never possible to achieve a 5 % dehumidification rate with 5 cfm. In general, the dehumidification rate was always limited and lower than 1 % for all the air flow rates considered and mainly within the uncertainty of the dew point sensors. These results confirmed the already limited predictions of the thermodynamics model, for ideal conditions and the interesting and promising results obtained in some experimental investigations available in the open literature were not achievable in this thesis. The more probable reasons were the higher air flow rates considered and the complete absence of the use of cooling power, which was mainly implemented to facilitate the vapor condensation.

Morcelli, Stefano↗

The EGS Collab Project – Stimulations at Two Depths

The EGS Collab project, supported by the US Department of Energy, is performing intensively monitored rock stimulation and flow tests at the 10-m scale in an underground research laboratory to address challenges in implementing enhanced geothermal systems (EGS). Data and observations from the field tests are compared to simulations to understand processes and build confidence in numerical modeling of the processes. We have completed Experiment 1 (of 3), which examined hydraulic fracturing in a well-characterized underground fractured phyllite test bed at a depth of approximately 1.5 km at the Sanford Underground Research Facility (SURF) in Lead, South Dakota. Testbed characterization included fracture mapping, borehole acoustic and optical televiewers, full waveform sonic, conductivity, resistivity, temperature, campaign p- and s-wave investigations and electrical resistance tomography. Borehole geophysical techniques including passive seismic, continuous active source seismic monitoring, electrical resistance tomography, fiber-based distributed strain, distributed temperature, and distributed acoustic monitoring, were used to carefully monitor stimulation events and flow tests. More than a dozen stimulations and nearly one year of flow tests were performed. Quality data and detailed observations were collected and analyzed during stimulation and water flow tests using ambient temperature and chilled water. We achieved adaptive control of the tests using real-time monitoring and rapid dissemination of data and near-real-time simulation. More detailed numerical simulation was performed to answer key experimental design questions, forecast fracture propagation trajectories and extents, and analyze and evaluate results. Data are freely available from the Geothermal Data Repository. Experiment 2 examines the potential for hydraulic shearing in amphibolite at a depth of about 1.25 km at SURF. This site has a different set of stress and fracture conditions than Experiment 1. The Experiment 2 testbed consists of nine subhorizontal boreholes configured in two fans of two boreholes which surround the testbed and contain grouted-in electrical resistance tomography, seismic sensors, active seismic sources and distributed fiber sensors. A “five-spot” set of test wells that extends from a custom mined alcove includes an injection well and four production/monitoring wells. The testbed was characterized geophysically and hydrologically, and three stimulations have been performed using the Step-Rate Injection Method for Fracture In-Situ Properties (SIMFIP) tool to measure strains, and a new strain quantifying tool (downhole robotic strain analysis tool -DORSA) was deployed in a monitoring hole during stimulation. Real-time data were broadcast during stimulations to allow real-time response to arising issues.

EGS Collab, Enhanced Geothermal Systems, EGS, fiel↗

Algorithms and file structures to enhance software workflows for ion mobility mass spectrometry (IM-MS)

Support customizations of algorithms and raw data file structures to enhance software workflows for liquid chromatography (LC), mass spectrometry (MS) and ion mobility mass spectrometry (IM-MS)-based metabolite characterization. Evaluate and improve the integration of ion mobility to existing MS analysis methods of the Mass Profiler Professional workflow (Mass Profiler, ID Browser and Mass Profiler Professional).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A multiscale anisotropic polymer network model coupled with phase field fracture

The study of polymers has continued to gain substantial attention due to their expanding range of applications, spanning essential engineering fields to emerging domains like stretchable electronics, soft robotics, and implantable sensors. These materials exhibit remarkable properties, primarily stemming from their intricate polymer chain network, which, in turn, increases the complexity of precisely modeling their behavior. Especially for modeling elastomers and their fracture behavior, accurately accounting for the deformations of the polymer chains is vital for predicting the rupture in highly stretched chains. Despite the importance, many robust multiscale continuum frameworks for modeling elastomer fracture tend to simplify network deformations by assuming uniform behavior among chains in all directions. Recognizing this limitation, our study proposes a multiscale fracture model that accounts for the anisotropic nature of elastomer network responses. At the microscale, damage in the chains is assumed to be driven by both the chain's entropy and the internal energy due to molecular bond distortions. In order to bridge the stretching in the chains to the macroscale deformation, we employ the maximal advance path constraint network model, inherently accommodating anisotropic network responses. As a result, chains oriented differently can be predicted to exhibit varying stretch and, consequently, different damage levels. To drive macroscale fracture based on damages in these chains, we utilize the micromorphic regularization theory, which involves the introduction of dual local-global damage variables at the macroscale. The macroscale local damage variable is obtained through the homogenization of the chain damage values, resulting in the prediction of an isotropic material response. The macroscale global damage variable is subjected to nonlocal effects and boundary conditions in a thermodynamically consistent phase field continuum formulation. Moreover, the total dissipation in the system is considered to be mainly due to the breaking of the molecular bonds at the microscale. To validate our model, we employ the double-edge notched tensile test as a benchmark, comparing simulation predictions with existing experimental data. Additionally, to enhance our understanding of the fracturing process, we conduct uniaxial tensile experiments on a square film made up of polydimethylsiloxane (PDMS) rubber embedded with a hole and notches and then compare our simulation predictions with the experimental observations. Furthermore, we visualize the evolution of stretch and damage values in chains oriented along different directions to assess the predictive capacity of the model. In conclusion, the results are also compared with another existing model to evaluate the utility of our model in accurately simulating the fracture behavior of rubber-like materials.

42 ENGINEERING↗

Search for long-lived heavy neutrinos in the decays of B mesons produced in proton-proton collisions at $ \sqrt{s} $ = 13 TeV

A search for long-lived heavy neutrinos (N) in the decays of B mesons produced in proton-proton collisions at $ \sqrt{s} $ = 13 TeV is presented. The data sample corresponds to an integrated luminosity of 41.6 fb$^{−1}$ collected in 2018 by the CMS experiment at the CERN LHC, using a dedicated data stream that enhances the number of recorded events containing B mesons. The search probes heavy neutrinos with masses in the range 1 < m$_{N}$ < 3 GeV and decay lengths in the range 10$^{−2}$ < cτ$_{N}$ < 10$^{4}$ mm, where τ$_{N}$ is the N proper mean lifetime. Signal events are defined by the signature B → ℓ$_{B}$NX; N → ℓ$^{±}$π$^{∓}$, where the leptons ℓ$_{B}$ and ℓ can be either a muon or an electron, provided that at least one of them is a muon. The hadronic recoil system, X, is treated inclusively and is not reconstructed. No significant excess of events over the standard model background is observed in any of the ℓ$^{±}$π$^{∓}$ invariant mass distributions. Limits at 95% confidence level on the sum of the squares of the mixing amplitudes between heavy and light neutrinos, |V$_{N}$|$^{2}$, and on cτ$_{N}$ are obtained in different mixing scenarios for both Majorana and Dirac-like N particles. The most stringent upper limit |V$_{N}$|$^{2}$ < 2.0 × 10$^{−5}$ is obtained at m$_{N}$ = 1.95 GeV for the Majorana case where N mixes exclusively with muon neutrinos. The limits on |V$_{N}$|$^{2}$ for masses 1 < m$_{N}$ < 1.7 GeV are the most stringent from a collider experiment to date.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Effect of neutron beamline irradiation on hydrogen equilibrium vapor pressure over hydrided Zircaloy-4

Here, the effect of neutron irradiation on the hydrogen equilibrium vapor pressure over hydrided samples of nickel-plated Zircaloy-4 was evaluated at the Washington State University Research Reactor’s epithermal beamline facility. To enable this study, a measurement capability was designed and assembled to obtain low pressure (<0.1 Pa) measurements over the temperature range of interest (i.e., ~300° - 400°C). Measurement results were in good agreement with tends extrapolated from previous data obtained at higher temperatures as well as recent thermodynamic data. No irradiation enhancement of vapor pressure was observed under the incident flux of epithermal neutrons over this temperature range.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Low-dimensional carbon materials decorated FAPbI 3 for carbon-based perovskite solar cells

Carbon nanomaterials are at the forefront of research in perovskite solar cells (PSCs) due to their exceptional electrical, optical, and stability properties. Their diverse applications include serving as interfacial layers, additives, hole and electron transport materials, and back electrodes. While the influence of various low-dimensional carbon nanomaterial structures on crystallinity, optical and electrical performance, and overall device efficiency has been a topic of interest, it has not been thoroughly explored until now. In this study, we effectively integrated carbon quantum dots (CQDs), multi-walled carbon nanotubes (MWCNTs), and graphene into the FAPbI 3 photoactive layer using a two-step sequential deposition method. Our experiments revealed marked improvements in the photovoltaic performance of PSCs that incorporated all three types of carbon nanomaterials. In particular, the data shows significant enhancements in power conversion efficiency, demonstrating the effectiveness of these materials in optimizing device functionality. Notably, MWCNTs distinguished themselves by exhibiting a remarkable potential for enhancing long-term stability. This finding underscores the importance of selecting the right carbon nanomaterials for future PSC developments, paving the way for more reliable and efficient solar energy solutions. As a result, our research highlights the critical role of carbon nanomaterials in advancing perovskite solar technology.

14 SOLAR ENERGY↗

Comparison of Machine Learning and Deep Learning for View Identification from Cardiac Magnetic Resonance Images

Background: Artificial intelligence is increasingly utilized to aid in the interpretation of cardiac magnetic resonance (CMR) studies. One of the first steps is the identification of the imaging plane depicted, which can be achieved by both deep learning (DL) and classical machine learning (ML) techniques without user input. We aimed to compare the accuracy of ML and DL for CMR view classification and to identify potential pitfalls during training and testing of the algorithms. Methods: To train our DL and ML algorithms, we first established datasets by retrospectively selecting 200 CMR cases. The models were trained using two different cohorts (passively and actively curated) and applied data augmentation to enhance training. Once trained, the models were validated on an external dataset, consisting of 20 cases acquired at another center. We then compared accuracy metrics and applied class activation mapping (CAM) to visualize DL model performance. Results: The DL and ML models trained with the passively-curated CMR cohort were 99.1% and 99.3% accurate on the validation set, respectively. However, when tested on the CMR cases with complex anatomy, both models performed poorly. After training and testing our models again on all 200 cases (active cohort), validation on the external dataset resulted in 95% and 90% accuracy, respectively. The CAM analysis depicted heat maps that demonstrated the importance of carefully curating the datasets to be used for training. Conclusions: Both DL and ML models can accurately classify CMR images, but DL outperformed ML when classifying images with complex heart anatomy.

artificial intelligence↗

Multi-faceted framework for extrapolating early age flexural strength to facilitate rapid lifting/handling of high-volume fly ash precast members

Maintaining adequate early-age structural performance for precast concrete components has grown in importance as more sustainable mix designs become more widespread. Achieving high-early flexural strength is particularly crucial to facilitate rapid removal of hardened concrete components from formwork, often within 24 h after fresh concrete placement. Limited research has assessed the effectiveness of traditional design methods in correlating flexural strength with compressive strength for next-generation mix designs, or demonstrated extrapolation of such material performance to larger-scale structural tests. This paper presents a multi-faceted framework to reassess early-age flexural strength for concretes made with relatively high proportions of fly ash from both fresh and harvested sources. Here, the framework provides several pathways, from which the user can select based upon available resources and the specific application, to improve accuracy of early-age cracking moment calculations. Furthermore, the scope includes evaluation of strength performance under curing conditions emulative of those in a precast facility, recommending modulus of rupture equations which are more performance-driven than current design provisions, and experimental tests on prefabricated concrete beams to validate the proposed methodologies. Correlations of early-age strength with both concrete age and maturity measurements compare the effectiveness of utilizing in-situ data to further enhance the prediction methods. Ultimately, the proposed framework helped reduce errors when calculating cracking moment capacity at early ages by tailoring calculations to reflect mix-dependent behavior. Furthermore, most estimates of cracking moment were within 25 % of their corresponding experimental test results, thus promoting confidence for using these strategies with high-volume fly ash precast structures.

42 ENGINEERING↗

Laser Ablation-Capillary Absorption Spectroscopy: A novel approach for high throughput and increased spatial resolution measurements of δ 13 C in plant-soil systems

Spatial and temporal heterogeneity of nutrient exchange within the rhizosphere is a topic of increasing interest, although challenging to study due to limits in existing analytical capabilities. Here, we developed and demonstrated a new approach applying laser ablation sample introduction to capillary absorption spectroscopy (LA-CAS) to characterize carbon isotopic distribution within plant tissues, rhizosphere, and soil. We exposed switchgrass plants to 13 CO 2 to allow tracing of 13 C-labelled photosynthates within plant biomass and into the associated soil. The LA-CAS methods we describe leverage continuous measurements of a sample stream derived from laser ablation line scans (10-25 µm in width) over a sample surface which enables the user to produce an isotope map with a) higher data density or b) over larger spatial areas versus previously existing techniques. This versatility of LA-CAS is assessed through testing of a range of laser parameters (spot size, scan rates) on various materials (soil, plant biomass/tissues, and rhizosphere). Here, we demonstrate the ability of LA-CAS to provide near instantaneous $δ$ 13 C measurements over isotopically distinct surfaces to enable high spatially resolved mapping of 13 C-labelled material within the rhizosphere. Applying LA-CAS analysis to plant biomass, we observed higher $δ$ 13 C values concentrated within phloem structures, consistent with localized photosynthate transport. When mapping across the rhizosphere, 13 C-enriched soil was typically present within 5-10µm of root boundaries with a steep spatial increase in $δ$ 13 C when the scan approached the middle of the root. As with all LA approaches, care is required to ensure accurate results as phenomena linked to ablation, combustion, and isotopic measurement can impart artifacts if not carefully controlled. Still, taken as a whole, our demonstrations highlight the increased sample throughput, improved data density, and enhanced $δ$ 13 C capability of LA-CAS versus other LA techniques and emphasize the role this method can play in future plant and rhizosphere related studies.

59 BASIC BIOLOGICAL SCIENCES↗

Foreword Special issue on the Kilopower Project, Kilowatt Reactor Using Stirling TechnologY (KRUSTY) Test

This special issue of Nuclear Technology contains full-length, peer-reviewed papers describing the design work leading up to and the results of the Kilowatt Reactor Using Stirling TechnologY (KRUSTY) test. KRUSTY was the centerpiece of the National Aeronautics and Space Administration (NASA) Kilopower Project to design, build, and test a space nuclear reactor. This test was the first such test since the end of the Space Nuclear Auxiliary Power (SNAP) project at the end of the 1960s. In this issue, the introduction paper presents the goals of the Kilopower Project and the potential missions this reactor concept could serve in NASA. Kilopower was intended to serve both human exploration needs on planetary surfaces as well as science needs for deep-space exploration. The design work for the experiment by Poston and the power conversion development by Gibson present the pre-work required to perform the eventual KRUSTY test. A paper on regulatory analysis follows, to show the path used to gain approval of the proposed experiment. Then, the early zero-power critical experiments are presented by Sanchez and Grove. These experiments were essential data used to enhance model predictions prior to the high-temperature test. Next, Poston presents the three experiments (warm criticals) that increase the temperature in an incremental fashion prior to the final experiment. These experiments were used to achieve final regulatory approval of the final high-temperature experiment. The last paper by Poston presents the results of the steady-state and transient testing of the reactor at full power and at the design temperature. These results show that the reactor design and as-built experiment met all of the requirements that NASA had developed for the system. Any experiment of this magnitude was accomplished only because of the hard work and dedication of a large number of people at multiple institutions, including the NASA Glenn Research Center, NASA Marshall Space Flight Center, Y-12 National Security Site, Los Alamos National Laboratory, and the Nevada National Security Site prime contractor (formerly National Security Technologies and now the Mission Support and Test Services). The project was jointly funded by the Space Technology Mission Directorate at NASA and the Criticality Safety Program at the National Nuclear Security Administration (NNSA). A special thanks to Jerry McKamy and Angela Chambers at the NNSA and Lee Mason and Don Palac at NASA for their support and guidance. For the authors and multitude of staff that performed this work, the passion for space nuclear reactors was the key to making this experiment a reality.

99 GENERAL AND MISCELLANEOUS↗

Sensitivity Analysis of Genome-Scale Metabolic Flux Prediction

TRIMER, Transcription Regulation Integrated with MEtabolic Regulation, is a genome-scale modeling pipeline targeting at metabolic engineering applications. Using TRIMER, regulated metabolic reactions can be effectively predicted by integrative modeling of metabolic reactions with a Transcription Factor (TF)-gene regulatory network (TRN), which is modeled via a Bayesian network (BN). In this paper, we focus on sensitivity analysis of metabolic flux prediction for uncertainty quantification of BN structures for TRN modeling in TRIMER. We propose a computational strategy to construct the uncertainty class of TRN models based on the inferred regulatory order uncertainty given transcriptomic expression data. With that, we analyze the prediction sensitivity of the TRIMER pipeline for the metabolite yields of interest. The obtained sensitivity analyses can guide Optimal Experimental Design (OED) to help acquire new data that can enhance TRN modeling and achieve specific metabolic engineering objectives, including metabolite yield alterations. Here we have performed small- and large-scale simulated experiments, demonstrating the effectiveness of our developed sensitivity analysis strategy for BN structure learning to quantify the edge importance in terms of metabolic flux prediction uncertainty reduction and its potential to effectively guide OED.

59 BASIC BIOLOGICAL SCIENCES↗

X-ray microscopy enables multiscale high-resolution 3D imaging of plant cells, tissues, and organs

Capturing complete internal anatomies of plant organs and tissues within their relevant morphological context remains a key challenge in plant science. While plant growth and development are inherently multiscale, conventional light, fluorescence, and electron microscopy platforms are typically limited to imaging of plant microstructure from small flat samples that lack a direct spatial context to, and represent only a small portion of, the relevant plant macrostructures. We demonstrate technical advances with a lab-based X-ray microscope (XRM) that bridge the imaging gap by providing multiscale high-resolution three-dimensional (3D) volumes of intact plant samples from the cell to the whole plant level. Serial imaging of a single sample is shown to provide sub-micron 3D volumes co-registered with lower magnification scans for explicit contextual reference. High-quality 3D volume data from our enhanced methods facilitate sophisticated and effective computational segmentation. Advances in sample preparation make multimodal correlative imaging workflows possible, where a single resin-embedded plant sample is scanned via XRM to generate a 3D cell-level map, and then used to identify and zoom in on sub-cellular regions of interest for high-resolution scanning electron microscopy. In total, we present the methodologies for use of XRM in the multiscale and multimodal analysis of 3D plant features using numerous economically and scientifically important plant systems.

59 BASIC BIOLOGICAL SCIENCES↗