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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Development of computational small animal models and their applications in preclinical imaging and therapy research

The development of multimodality preclinical imaging techniques and the rapid growth of realistic computer simulation tools have promoted the construction and application of computational laboratory animal models in preclinical research. Since the early 1990s, over 120 realistic computational animal models have been reported in the literature and used as surrogates to characterize the anatomy of actual animals for the simulation of preclinical studies involving the use of bioluminescence tomography, fluorescence molecular tomography, positron emission tomography, single-photon emission computed tomography, microcomputed tomography, magnetic resonance imaging, and optical imaging. Other applications include electromagnetic field simulation, ionizing and nonionizing radiation dosimetry, and the development and evaluation of new methodologies for multimodality image coregistration, segmentation, and reconstruction of small animal images. This paper provides a comprehensive review of the history and fundamental technologies used for the development of computational small animal models with a particular focus on their application in preclinical imaging as well as nonionizing and ionizing radiation dosimetry calculations. An overview of the overall process involved in the design of these models, including the fundamental elements used for the construction of different types of computational models, the identification of original anatomical data, the simulation tools used for solving various computational problems, and the applications of computational animal models in preclinical research. The authors also analyze the characteristics of categories of computational models (stylized, voxel-based, and boundary representation) and discuss the technical challenges faced at the present time as well as research needs in the future.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2024

Synthesizing realistic sand assemblies with denoising diffusion in latent space

Abstract The shapes and morphological features of grains in sand assemblies have far‐reaching implications in many engineering applications, such as geotechnical engineering, computer animations, petroleum engineering, and concentrated solar power. Yet, our understanding of the influence of grain geometries on macroscopic response is often only qualitative, due to the limited availability of high‐quality 3D grain geometry data. In this paper, we introduce a denoising diffusion algorithm that uses a set of point clouds collected from the surface of individual sand grains to generate grains in the latent space. By employing a point cloud autoencoder, the three‐dimensional point cloud structures of sand grains are first encoded into a lower‐dimensional latent space. A generative denoising diffusion probabilistic model is trained to produce synthetic sand that maximizes the log‐likelihood of the generated samples belonging to the original data distribution measured by a Kullback‐Leibler divergence. Numerical experiments suggest that the proposed method is capable of generating realistic grains with morphology, shapes and sizes consistent with the training data inferred from an F50 sand database. We then use a rigid contact dynamic simulator to pour the synthetic sand in a confined volume to form granular assemblies in a static equilibrium state with targeted distribution properties. To ensure third‐party validation, 50,000 synthetic sand grains and the 1542 real synchrotron microcomputed tomography (SMT) scans of the F50 sand, as well as the granular assemblies composed of synthetic sand grains are made available in an open‐source repository.

Vlassis, Nikolaos N.↗
DOE OSTI2013

Hydrogen Technology and Energy Curriculum (HyTEC)

The Lawrence Hall of Science of the University of California, Berkeley has collaborated with scientists and engineers, a local transit agency, school districts, and a commercial curriculum publisher to develop, field-test nationally, and publish a two-week curriculum module on hydrogen and fuel cells for high school science. Key partners in this project are the Schatz Energy Research Center (SERC) of Humboldt State University, the Alameda-Contra Costa Transit District (AC Transit), FilmSight Productions, Lab-Aids, Inc., and 32 teachers and 2,370 students in field-test classrooms in California, Connecticut, Ohio, New York, South Carolina, and Washington. Field-test teachers received two to three days of professional development before teaching the curriculum and providing feedback used for revision of the curriculum. The curriculum, titled Investigating Alternative Energy: Hydrogen and Fuel Cells and published by Lab-Aids, Inc., includes a teachers guide (with lesson plans, resources, and student handout pages), two interactive computer animations, a video, a website, and a laboratory materials kit. The project has been disseminated to over 950 teachers through awareness workshops at state, regional, and national science teacher conferences.

08 HYDROGEN↗
DOE OSTI2023

Wassersplines for Neural Vector Field-Controlled Animation

Much of computer-generated animation is created by manipulating meshes with rigs. While this approach works well for animating articulated objects like animals, it has limited flexibility for animating less structured free-form objects. Here we introduce Wassersplines, a novel trajectory inference method for animating unstructured densities based on recent advances in continuous normalizing flows and optimal transport. The key idea is to train a neurally-parameterized velocity field that represents the motion between keyframes. Trajectories are then computed by advecting keyframes through the velocity field. We solve an additional Wasserstein barycenter interpolation problem to guarantee strict adherence to keyframes. Our tool can stylize trajectories through a variety of PDE-based regularizers to create different visual effects. We demonstrate our tool on various keyframe interpolation problems to produce temporally-coherent animations without meshing or rigging.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

The Graph Laplacian and the Dynamics of Complex Networks [Slides]

In this talk, we explore the structure of networks from a spectral graph-theoretic perspective by analyzing the properties of the Laplacian matrix associated with the graph induced by a network. We will see how the eigenvalues of the graph Laplacian relate to the underlying network structure and dynamics and provides insight into a phenomenon frequently observed in real world networks - the emergence of collective behavior from purely local interactions seen in the coordinated motion of animals and phase transitions in biological networks, to name a few.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Nonlinear optimization for a tumor invasion PDE model

In this work, we introduce a methodology to approximate unknown parameters that appear on a non-linear reaction–diffusion model of tumor invasion. These equations consider that tumor-induced alteration of micro-environmental pH furnishes a mechanism for cancer invasion. A coupled system reaction–diffusion explaining this model is given by three partial differential equations for the non-dimensional spatial distribution and temporal evolution of the density of normal tissue, the neoplastic tissue growth and the excess concentration of H{sup +} ions. The tumor model parameters have a corresponding biological meaning: the reabsorption rate, the destructive influence of H{sup +} ions in the healthy tissue, the growth rate of tumor tissue and the diffusion coefficient. We propose to solve the direct problem using the Finite Element Method (FEM) and minimize an appropriate functional including both the real data (obtained via in-vitro experiments and fluorescence ratio imaging microscopy) and the numerical solution. The gradient of the functional is computed by the adjoint method.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Adaptive scapula bone remodeling computational simulation: Relevance to regenerative medicine

Shoulder arthroplasty success has been attributed to many factors including, bone quality, soft tissue balancing, surgeon experience, and implant design. Improved long-term success is primarily limited by glenoid implant loosening. Prosthesis design examines materials and shape and determines whether the design should withstand a lifetime of use. Finite element (FE) analyses have been extensively used to study stresses and strains produced in implants and bone. However, these static analyses only measure a moment in time and not the adaptive response to the altered environment produced by the therapeutic intervention. Computational analyses that integrate remodeling rules predict how bone will respond over time. Recent work has shown that subject-specific two- and three dimensional adaptive bone remodeling models are feasible and valid. Feasibility and validation were achieved computationally, simulating bone remodeling using an intact human scapula, initially resetting the scapular bone material properties to be uniform, numerically simulating sequential loading, and comparing the bone remodeling simulation results to the actual scapula’s material properties. Three-dimensional scapula FE bone model was created using volumetric computed tomography images. Muscle and joint load and boundary conditions were applied based on values reported in the literature. Internal bone remodeling was based on element strain-energy density. Initially, all bone elements were assigned a homogeneous density. All loads were applied for 10 iterations. After every iteration, each bone element’s remodeling stimulus was compared to its corresponding reference stimulus and its material properties modified. The simulation achieved convergence. At the end of the simulation the predicted and actual specimen bone apparent density were plotted and compared. Location of high and low predicted bone density was comparable to the actual specimen. High predicted bone density was greater than actual specimen. Low predicted bone density was lower than actual specimen. Differences were probably due to applied muscle and joint reaction loads, boundary conditions, and values of constants used. Work is underway to study this. Nonetheless, the results demonstrate three dimensional bone remodeling simulation validity and potential. Such adaptive predictions take physiological bone remodeling simulations one step closer to reality. Computational analyses are needed that integrate biological remodeling rules and predict how bone will respond over time. We expect the combination of computational static stress analyses together with adaptive bone remodeling simulations to become effective tools for regenerative medicine research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

110th Anniversary : Thermal Coupling via Heat Transfer: A Potential Route to Simple Distillation Configurations with Lower Heat Duty

Numerous configurations are available for the separation of a multicomponent mixture by distillation; each of which has different energy requirements. Here, we classify heat integration (a valuable method of reducing energy requirements) within distillation into two categories: conventional thermal coupling with mass exchange between columns (TCM) and thermal coupling via heat transfer without mass exchange (TCH). The sharp split distillation configurations, with the lowest number of distillation sections and transfer streams, provide simple distillation configurations but are known to have heat duties that are much higher than the fully thermally coupled (FTC) or Petlyuk configuration. However, for a mixture with four or more components, FTC, having the maximum number of column sections, is a complex configuration to build and operate. Through specific examples of four and five component distillations, we present, for the first time, sharp split configurations, using only one TCH and no TCM, which have a lower heat duty than the corresponding FTC containing only TCM, without requiring substantial pressure changes in the system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Light field moment imaging with the ptychographic iterative engine

The recently developed Light Field Moment Imaging (LMI) is adopted to show the stereoscopic structure of the sample studied in Coherent Diffractive Imaging (CDI), where 3D image were always generated with complicated experimental procedure such as the rotation of the sample and time-consuming computation. The animation of large view angle can be generated with LMI very quickly, and the 3D structure of sample can be shown vividly. This method can find many applications for the coherent diffraction imaging with x-ray and electron beams, where a glimpse of the hierarchical structure required and the quick and simple 3D view of object is sufficient. The feasibility of this method is demonstrated theoretically and experimentally with a recently developed CDI method called Ptychographic Iterative Engine.

36 MATERIALS SCIENCE↗
DOE OSTI2010

Ames Lab 101: VE-Suite

Ames Laboratory scientist Mark Bryden talks about virtual engineering and the advantages it gives engineers when they can "walk through" designs visually.

42 ENGINEERING↗
DOE OSTI2014

Impact of extraneous mispositioned events on motion-corrected brain SPECT images of freely moving animals

Purpose: Single photon emission computed tomography (SPECT) brain imaging of freely moving small animals would allow a wide range of important neurological processes and behaviors to be studied, which are normally inhibited by anesthetic drugs or precluded due to the animal being restrained. While rigid body motion of the head can be tracked and accounted for in the reconstruction, activity in the torso may confound brain measurements, especially since motion of the torso is more complex (i.e., nonrigid) and not well correlated with that of the head. The authors investigated the impact of mispositioned events and attenuation due to the torso on the accuracy of motion corrected brain images of freely moving mice. Methods: Monte Carlo simulations of a realistic voxelized mouse phantom and a dual compartment phantom were performed. Each phantom comprised a target and an extraneous compartment which were able to move independently of each other. Motion correction was performed based on the known motion of the target compartment only. Two SPECT camera geometries were investigated: a rotating single head detector and a stationary full ring detector. The effects of motion, detector geometry, and energy of the emitted photons (hence, attenuation) on bias and noise in reconstructed brain regions were evaluated. Results: The authors observed two main sources of bias: (a) motion-related inconsistencies in the projection data and (b) the mismatch between attenuation and emission. Both effects are caused by the assumption that the orientation of the torso is difficult to track and model, and therefore cannot be conveniently corrected for. The motion induced bias in some regions was up to 12% when no attenuation effects were considered, while it reached 40% when also combined with attenuation related inconsistencies. The detector geometry (i.e., rotating vs full ring) has a big impact on the accuracy of the reconstructed images, with the full ring detector being more advantageous. Conclusions: Motion-induced inconsistencies in the projection data and attenuation/emission mismatch are the two main causes of bias in reconstructed brain images when there is complex motion. It appears that these two factors have a synergistic effect on the qualitative and quantitative accuracy of the reconstructed images.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Computer-aided pulmonary image analysis in small animal models

Purpose: To develop an automated pulmonary image analysis framework for infectious lung diseases in small animal models. Methods: The authors describe a novel pathological lung and airway segmentation method for small animals. The proposed framework includes identification of abnormal imaging patterns pertaining to infectious lung diseases. First, the authors’ system estimates an expected lung volume by utilizing a regression function between total lung capacity and approximated rib cage volume. A significant difference between the expected lung volume and the initial lung segmentation indicates the presence of severe pathology, and invokes a machine learning based abnormal imaging pattern detection system next. The final stage of the proposed framework is the automatic extraction of airway tree for which new affinity relationships within the fuzzy connectedness image segmentation framework are proposed by combining Hessian and gray-scale morphological reconstruction filters. Results: 133 CT scans were collected from four different studies encompassing a wide spectrum of pulmonary abnormalities pertaining to two commonly used small animal models (ferret and rabbit). Sensitivity and specificity were greater than 90% for pathological lung segmentation (average dice similarity coefficient > 0.9). While qualitative visual assessments of airway tree extraction were performed by the participating expert radiologists, for quantitative evaluation the authors validated the proposed airway extraction method by using publicly available EXACT’09 data set. Conclusions: The authors developed a comprehensive computer-aided pulmonary image analysis framework for preclinical research applications. The proposed framework consists of automatic pathological lung segmentation and accurate airway tree extraction. The framework has high sensitivity and specificity; therefore, it can contribute advances in preclinical research in pulmonary diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

High-resolution short-exposure small-animal laboratory x-ray phase-contrast tomography

X-ray computed tomography of small animals and their organs is an essential tool in basic and preclinical biomedical research. In both phase-contrast and absorption tomography high spatial resolution and short exposure times are of key importance. However, the observable spatial resolutions and achievable exposure times are presently limited by system parameters rather than more fundamental constraints like, e.g., dose. Here we demonstrate laboratory tomography with few-ten μm spatial resolution and few-minute exposure time at an acceptable dose for small-animal imaging, both with absorption contrast and phase contrast. The method relies on a magnifying imaging scheme in combination with a high-power small-spot liquid-metal-jet electron-impact source. Lastly, the tomographic imaging is demonstrated on intact mouse, phantoms and excised lungs, both healthy and with pulmonary emphysema.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Forecasting climate change impacts on plant populations over large spatial extents

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Radiobiology, Omics and Microdosimetry of Systemic and Targeted Radiotherapeutics Workshop

The Radiobiology, Omics and Microdosimetry of Systemic and Targeted Radiotherapeutics Workshop fostered engagement across disciplines on critical topics that impact the development of targeted radionuclide therapies, bringing together scientific and medical professionals actively involved in radiotherapeutic design, optimization testing, patient treatment, and clinical trials along with basic science researchers, whose novel techniques have the potential to further our understanding of targeted radionuclide therapy. Discussion of the applications of radiotherapeutics to pediatric and adult, brain, prostate and blood cancers, and metastatic disease allowed scientific research to be presented in the context of real-world medical applications and provided an important backdrop to the basic research performed in computers, laboratories, and animal facilities. The workshop format, presentations, and panel discussions were designed to consider a holistic approach to the development of systemic and targeted radiotherapies, integrating radiobiology and microdosimetry, biological assessments on the microscale, and physiologically relevant models of tumor and tissue microenvironments. Important needs highlighted in the workshop include better models to assess the biological effects of radionuclide therapy, novel strategies to target radiotherapeutics to disease sites with high specificity, and new dosimetry techniques that address the importance of tumor microenvironments.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

On the Green's function of the partially diffusion-controlled reversible ABCD reaction for radiation chemistry codes

Several computer codes simulating chemical reactions in particles systems are based on the Green's functions of the diffusion equation (GFDE). Indeed, many types of chemical systems have been simulated using the exact GFDE, which has also become the gold standard for validating other theoretical models. In this work, a simulation algorithm is presented to sample the interparticle distance for partially diffusion-controlled reversible ABCD reaction. This algorithm is considered exact for 2-particles systems, is faster than conventional look-up tables and uses only a few kilobytes of memory. The simulation results obtained with this method are compared with those obtained with the independent reaction times (IRT) method. This work is part of our effort in developing models to understand the role of chemical reactions in the radiation effects on cells and tissues and may eventually be included in event-based models of space radiation risks. However, as many reactions are of this type in biological systems, this algorithm might play a pivotal role in future simulation programs not only in radiation chemistry, but also in the simulation of biochemical networks in time and space as well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Stable Small Animal Mechanical Ventilation for Dynamic Lung Imaging to Support Computational Fluid Dynamics Models

Pulmonary computational fluid dynamics models require 3D images to be acquired over multiple points in the dynamic breathing cycle, with no breath holds or changes in ventilatory mechanics. With small animals, these requirements result in long imaging times ({approx}90 minutes), over which lung mechanics, such as compliance, can gradually change if not carefully monitored and controlled. These changes, caused by derecruitment of parenchymal tissue, are manifested as an upward drift in peak inspiratory pressure or by changes in the pressure waveform and/or lung volume over the course of the experiment. We demonstrate highly repeatable mechanical ventilation in anesthetized rats over a long duration for pulmonary CT imaging throughout the dynamic breathing cycle. We describe significant updates to a basic commercial ventilator that was acquired for these experiments. Key to achieving consistent results was the implementation of periodic deep breaths, or sighs, of extended duration to maintain lung recruitment. In addition, continuous monitoring of breath-to-breath pressure and volume waveforms and long-term trends in peak inspiratory pressure and flow provide diagnostics of changes in breathing mechanics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Final Report for NMBSA Project, Monika Kaden, 2016

The following pages define the objectives and results for Project 022, requested by Monika Kaden, a sculptor who maintains studios in Santa Fe. This effort was first approved in February 2016, and was completed during several different time segments spread over the year, depending on Monika’s availability. The project deliverables that are of primary use to the customer are digital data files that are to be delivered electronically. This report is a summary overview of how the project was conducted.

97 MATHEMATICS AND COMPUTING↗