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At least 469 records · Page 26

Microgravity-Induced Physiological Fluid Redistribution: Computational Analysis to Assess Influence of Physiological Parameters

Space flight impacts human physiology in many ways, the most immediate being the marked cephalad (headward) shift of fluid upon introduction into the microgravity environment. This physiological response to microgravity points to the redistribution of blood and interstitial fluid as a major factor in the loss of venous tone and reduction in heart muscle efficiency which impact astronaut performance. In addition, researchers have hypothesized that a reduction in astronaut visual acuity, part of the Visual Impairment and Intracranial Pressure (VIIP) syndrome, is associated with this redistribution of fluid. VIIP arises within several months of beginning space flight and includes a variety of ophthalmic changes including posterior globe flattening, distension of the optic nerve sheath, and kinking of the optic nerve. We utilize a suite of lumped parameter models to simulate microgravity-induced fluid redistribution in the cardiovascular, central nervous and ocular systems to provide initial and boundary data to a 3D finite element simulation of ocular biomechanics in VIIP. Specifically, the lumped parameter cardiovascular model acts as the primary means of establishing how microgravity, and the associated lack of hydrostatic gradient, impacts fluid redistribution. The cardiovascular model consists of 16 compartments, including three cerebrospinal fluid (CSF) compartments, three cranial blood compartments, and 10 thoracic and lower limb blood compartments. To assess the models capability to address variations in physiological parameters, we completed a formal uncertainty and sensitivity analysis that evaluated the relative importance of 42 input parameters required in the model on relative compartment flows and compartment pressures. Utilizing the model in a pulsatile flow configuration, the sensitivity analysis identified the ten parameters that most influenced each compartment pressure. Generally, each compartment responded appropriately to parameter variations associated with itself and adjacent compartments. However, several unexpected interactions between components, such as between the choroid plexus and the lower capillaries, were found, and are due to simplifications in the formulation of the model. The analysis illustrates that highly influential parameters and those that have unique influences within the model formulation must be tightly controlled for successful model application.

gravitational physiology↗

A ROS-based Simulator for Testing the Enhanced Autonomous Navigation of the Mars 2020 Rover

In order to achieve the ambitious objectives of the Mars 2020 (M2020) mission, in particular the ability to autonomously traverse more challenging terrains more efficiently, new surface mobility software was developed for Enhanced Navigation (ENav). That decision was made early in the project, before most of the new surface flight software (FSW) existed, which created a need for a separate framework where the new navigation algorithms could be quickly prototyped and tested, before more realistic FSW-based testbeds became available. The JPL robotics team chose the Robot Operating System [1] (ROS) as the environment in which to test the new ENav algorithms. This made it possible to write the algorithms in the C language required by the FSW, so they could be directly ported over to the flight module later on, while leveraging all the C++ libraries and tools provided by ROS for simulation and testing. The ENav algorithms were developed as a separate C library, and stubs were used to replace any FSW-specific code, such as Event Reporting (EVRs) and data products (DPs). A ROS simulator was developed to generate a rich set of varied 3D terrains representative of the candidate Mars landing sites and simulate the physics of the rover motion, the point cloud perceived by the rover’s stereo vision system, and the new thinking-while-driving (TWD) navigation logic which directs the rover to drive autonomously to user-specified waypoints. To simulate the rover motion and perception, a ROS node was developed that uses a software library called HyperDrive Sim (HDSim), which is a wrapper for the Rover Sequencing and Visualization Program [2] (RSVP). That library provides roverterrain settling, realistic slip modelling, and camera rendering capability based on the rover’s NavCam machine vision models. To simulate the navigation logic, a ROS node was created that initializes and runs the ENav algorithms in a way that mimics the FSW execution, while also providing the capability to load and replay data products, including re-running the recorded inputs through the ENav algorithms for testing. An engineering Graphical User Interface (GUI) was also developed to visualize various elements, such as the rover pose during the drive, the simulated and perceived terrain, the selected local and global paths to the goal, the evaluated candidate paths and the reasons why they were rejected, the keep-in and keep-out zones (KIOZs), etc. Finally, an advanced Monte Carlo (MC) framework that can run many simulations in parallel on the Cloud and automatically generate reports that capture the key ENav performance metrics was developed to evaluate the system in a statisticallymeaningful way. This paper provides an overview of the ROSbased simulator used for testing the M2020 ENav algorithms.

Toupet, Olivier↗

Parallel Finite Element Solution of 3D Rayleigh-Benard-Marangoni Flows

A domain decomposition strategy and parallel gradient-type iterative solution scheme have been developed and implemented for computation of complex 3D viscous flow problems involving heat transfer and surface tension effects. Details of the implementation issues are described together with associated performance and scalability studies. Representative Rayleigh-Benard and microgravity Marangoni flow calculations and performance results on the Cray T3D and T3E are presented. The work is currently being extended to tightly-coupled parallel "Beowulf-type" PC clusters and we present some preliminary performance results on this platform. We also describe progress on related work on hierarchic data extraction for visualization.

Carey, G. F.↗

Enhanced Line Integral Convolution with Flow Feature Detection

The Line Integral Convolution (LIC) method, which blurs white noise textures along a vector field, is an effective way to visualize overall flow patterns in a 2D domain. The method produces a flow texture image based on the input velocity field defined in the domain. Because of the nature of the algorithm, the texture image tends to be blurry. This sometimes makes it difficult to identify boundaries where flow separation and reattachments occur. We present techniques to enhance LIC texture images and use colored texture images to highlight flow separation and reattachment boundaries. Our techniques have been applied to several flow fields defined in 3D curvilinear multi-block grids and scientists have found the results to be very useful.

Lane, David↗

Unique life sciences research facilities at NASA Ames Research Center

The Life Science Division at NASA's Ames Research Center has a suite of specialized facilities that enable scientists to study the effects of gravity on living systems. This paper describes some of these facilities and their use in research. Seven centrifuges, each with its own unique abilities, allow testing of a variety of parameters on test subjects ranging from single cells through hardware to humans. The Vestibular Research Facility allows the study of both centrifugation and linear acceleration on animals and humans. The Biocomputation Center uses computers for 3D reconstruction of physiological systems, and interactive research tools for virtual reality modeling. Psycophysiological, cardiovascular, exercise physiology, and biomechanical studies are conducted in the 12 bed Human Research Facility and samples are analyzed in the certified Central Clinical Laboratory and other laboratories at Ames. Human bedrest, water immersion and lower body negative pressure equipment are also available to study physiological changes associated with weightlessness. These and other weightlessness models are used in specialized laboratories for the study of basic physiological mechanisms, metabolism and cell biology. Visual-motor performance, perception, and adaptation are studied using ground-based models as well as short term weightlessness experiments (parabolic flights). The unique combination of Life Science research facilities, laboratories, and equipment at Ames Research Center are described in detail in relation to their research contributions.

Mulenburg, G. M.↗

Enhancing Cluster Identification in Atom Probe Tomography Data Using Transfer Learning

Atom Probe Tomography (APT) is a powerful technique for visualizing the atomic-scale distribution of solutes in materials, but quantitative cluster analysis of APT datasets remains a challenge due to the need for subjective parameter selection in clustering algorithms. While distance-based and density-based methods such as HDBSCAN are widely used, their performance is highly sensitive to user-defined parameters, which undermines reproducibility and accuracy. This study proposes an image-based, deep learning-aided workflow for automating parameter selection and cluster detection in APT data analysis. By projecting 3D APT point clouds onto 2D planes, we leverage pretrained convolutional neural networks (ConvNeXt-Tiny and ResNet-50) through transfer learning to predict the number of clusters present in synthetic datasets. The output is used to guide K-means clustering and estimate HDBSCAN parameters, specifically minimum cluster size and minimum sample points. This approach reduces reliance on manual parameter tuning, improving consistency and scalability. The methodology demonstrates the feasibility of using image-based deep learning for interpreting complex spatial patterns in APT data, enabling faster and more objective analysis. The complete workflow and code are made publicly available to support reproducibility and future research.

Density-based clustering↗

Geometric Interpretation of the Cluster Location Problem Part I: Theory

We present a new framing of the seismic location problem using principles drawn from differential geometry. Our interpretation relies upon the common assumption that travel times observed across a network are continuous, differentiable functions of source location. In consequence, travel‐time functions constitute a differentiable map between the source region and a Riemannian manifold. The manifold is said to be the image of the source region embedded in a generally high‐dimension travel‐time vector space. A cluster of events in the source region has an image of discrete points on the manifold, that, except in the simplest cases, cannot be viewed directly. However, it is possible to project the image of a cluster into a tangent space of the manifold for direct visualization. The projection operator can be computed directly from the data without a velocity model, but produces a distorted rendering of the cluster geometry. With a model we can predict the distortions and correct them to estimate cluster geometry. We develop these points with the simplest possible example, one for which direct visualization of the manifold is possible, using the example as an introduction to the relevant concepts from differential geometry in a familiar setting. The tangent space, a local linearization of the manifold, plays a key role. We develop a metric to estimate the limits of linearization, that is, to determine when the curvature of the manifold invalidates the linear assumption. We also examine the interplay of model error, inadequate network geometry, and pick error. We then generalize our results from the simple case to the general case of 3D source regions observed by general networks. Although we do suggest a new “project and correct” method for location, we do not develop it into a practical algorithm. In conclusion, our intention rather is to highlight new analytical methods grounded in differential geometry.

East Pacific Ocean Islands↗

Integrated positron emission particle tracking (PEPT) and X-ray computed tomography (CT) imaging of flow phenomena in twisted tape swirl flow

Abstract A combined positron emission particle tracking (PEPT) and X-ray computed tomography (CT) technique is presented, and its utility is demonstrated through investigation of flow in a pipe with twisted tape swirl insert with varying flow conditions (diameter-based Reynolds numbers 16,300–63,300). A description of this technique is given, as well as data handling practices used to relate geometric information captured by CT to fluid flow data gathered via PEPT. It is found that the CT component is readily capable of capturing the stainless steel insert geometry in this present system, but the use of combined plastic and metal materials leads to artifacts in imaging of the plastic surface. Nonetheless, CT data are related to PEPT flow measurements, and average velocity fields are calculated via a pseudo-framing and interpolation scheme and used to visualize and interrogate key flow phenomena within the system. Radial velocity profiles of the mean flow characteristics are seen to collapse to a nearly common form across all flow conditions considered. Helical vortices are seen propagating through the flow field, generated by bypass flow around the gap between the insert and pipe wall, with additional coherent secondary flow structures seen in the higher Reynolds number cases. These findings enhance the understanding of the mixing mechanisms in these swirl flows and encourage the continued development of PEPT-CT methodologies for 3D flow measurements in optically inaccessible systems.

42 ENGINEERING↗

A Three-Dimensional Receiver Operator Characteristic Surface Diagnostic Metric

Receiver Operator Characteristic (ROC) curves are commonly applied as metrics for quantifying the performance of binary fault detection systems. An ROC curve provides a visual representation of a detection system s True Positive Rate versus False Positive Rate sensitivity as the detection threshold is varied. The area under the curve provides a measure of fault detection performance independent of the applied detection threshold. While the standard ROC curve is well suited for quantifying binary fault detection performance, it is not suitable for quantifying the classification performance of multi-fault classification problems. Furthermore, it does not provide a measure of diagnostic latency. To address these shortcomings, a novel three-dimensional receiver operator characteristic (3D ROC) surface metric has been developed. This is done by generating and applying two separate curves: the standard ROC curve reflecting fault detection performance, and a second curve reflecting fault classification performance. A third dimension, diagnostic latency, is added giving rise to 3D ROC surfaces. Applying numerical integration techniques, the volumes under and between the surfaces are calculated to produce metrics of the diagnostic system s detection and classification performance. This paper will describe the 3D ROC surface metric in detail, and present an example of its application for quantifying the performance of aircraft engine gas path diagnostic methods. Metric limitations and potential enhancements are also discussed

Simon, Donald L.↗

Three Dimensional Computer Graphics Federates for the 2012 Smackdown Simulation

The Simulation Interoperability Standards Organization (SISO) Smackdown is a two-year old annual event held at the 2012 Spring Simulation Interoperability Workshop (SIW). A primary objective of the Smackdown event is to provide college students with hands-on experience in developing distributed simulations using High Level Architecture (HLA). Participating for the second time, the University of Alabama in Huntsville (UAHuntsville) deployed four federates, two federates simulated a communications server and a lunar communications satellite with a radio. The other two federates generated 3D computer graphics displays for the communication satellite constellation and for the surface based lunar resupply mission. Using the Light-Weight Java Graphics Library, the satellite display federate presented a lunar-texture mapped sphere of the moon and four Telemetry Data Relay Satellites (TDRS), which received object attributes from the lunar communications satellite federate to drive their motion. The surface mission display federate was an enhanced version of the federate developed by ForwardSim, Inc. for the 2011 Smackdown simulation. Enhancements included a dead-reckoning algorithm and a visual indication of which communication satellite was in line of sight of Hadley Rille. This paper concentrates on these two federates by describing the functions, algorithms, HLA object attributes received from other federates, development experiences and recommendations for future, participating Smackdown teams.

Fordyce, Crystal↗

Global Solar Activity Data Portal for Studying 3D Dynamics and Activity of the Sun

The main problems with understanding and predicting solar activity are tightly linked to limitations in describing the global evolution of the Sun from the deep interior to the corona. Because of the complexity of interactions in a wide range of dynamical, turbulent, and spatial scales and dramatic changes in thermodynamic and magnetic field conditions, only physics-based models can provide essential background to generate reliable solar activity forecasts. However, performing accurate model calibration and estimating uncertainties is often challenging due to the unavailability of a long time series of observations. To mitigate these limitations, we have developed the Global Solar Activity (GSA) Data Portal, which enables convenient access to a variety of modern and historical data. The portal supports a dynamic visualization for 1D time series (such as the sunspot number and solar irradiance) and quick-look visualization for 2D datasets (e.g., synoptic magnetograms, the solar internal rotation, and flows). The GSA portal includes a search engine that enables data retrieval from user-specified data sources and time intervals. In this presentation, we will discuss the current and upcoming capabilities of the data portal and its potential applications for space weather studies.

SMD↗

Measurement Techniques for Hypervelocity Impact Test Fragments

The ability to classify the size and shape of individual orbital debris fragments provides a better understanding of the orbital debris environment as a whole. The characterization of breakup fragmentation debris has gradually evolved from a simplistic, spherical assumption towards that of describing debris in terms of size, material, and shape parameters. One of the goals of the NASA Orbital Debris Program Office is to develop high-accuracy techniques to measure these parameters and apply them to orbital debris observations. Measurement of the physical characteristics of debris resulting from groundbased, hypervelocity impact testing provides insight into the shapes and sizes of debris produced from potential impacts in orbit. Current techniques for measuring these ground-test fragments require determination of dimensions based upon visual judgment. This leads to reduced accuracy and provides little or no repeatability for the measurements. With the common goal of mitigating these error sources, allaying any misunderstandings, and moving forward in fragment shape determination, the NASA Orbital Debris Program Office recently began using a computerized measurement system. The goal of using these new techniques is to improve knowledge of the relation between commonly used dimensions and overall shape. The immediate objective is to scan a single fragment, measure its size and shape properties, and import the fragment into a program that renders a 3D model that adequately demonstrates how the object could appear in orbit. This information would then be used to aid optical methods in orbital debris shape determination. This paper provides a description of the measurement techniques used in this initiative and shows results of this work. The tradeoffs of the computerized methods are discussed, as well as the means of repeatability in the measurements of these fragments. This paper serves as a general description of methods for the measurement and shape analysis of orbital debris.

Hill, Nicole E.↗

Stereo Vision-Based Obstacle Avoidance for Micro Air Vehicles Using an Egocylindrical Image Space Represntation

Micro air vehicles which operate autonomously at low altitude in cluttered environments require a method for on-board obstacle avoidance for safe operation. Prior approaches can be divided between purely reactive approaches, mapping low-level visual features directly to headings to maneuver the vehicle around the obstacle, and deliberative methods that use on-board 3-D sensors to create a 3-D, voxel-based world model, which is then used to generate collision free 3-D trajectories. In this paper, we use forward-looking stereo vision with a large horizontal and vertical field of view and project range from stereo into a novel robot-centered, cylindrical, inverse range map we call an egocylinder. With this implementation we reduce the complexity of our world representation from a 3D map to a 2.5D image space representation, which supports very efficient motion planning and collision-checking. Configuration space expansion is done very efficiently on the egocylinder as an image processing function. Deploying a fast reactive motion planner directly on the configuration space expanded egocylinder image, we demonstrate the effectiveness of this new approach experimentally in an indoor environment.

Micro air vehicles↗

Subcellular Feature-Based Classification of α and β Cells Using Soft X-ray Tomography

The dysfunction of α and β cells in pancreatic islets can lead to diabetes. Many questions remain on the subcellular organization of islet cells during the progression of disease. Existing three-dimensional cellular mapping approaches face challenges such as time-intensive sample sectioning and subjective cellular identification. To address these challenges, we have developed a subcellular feature-based classification approach, which allows us to identify α and β cells and quantify their subcellular structural characteristics using soft X-ray tomography (SXT). We observed significant differences in whole-cell morphological and organelle statistics between the two cell types. Additionally, we characterize subtle biophysical differences between individual insulin and glucagon vesicles by analyzing vesicle size and molecular density distributions, which were not previously possible using other methods. These sub-vesicular parameters enable us to predict cell types systematically using supervised machine learning. We also visualize distinct vesicle and cell subtypes using Uniform Manifold Approximation and Projection (UMAP) embeddings, which provides us with an innovative approach to explore structural heterogeneity in islet cells. This methodology presents an innovative approach for tracking biologically meaningful heterogeneity in cells that can be applied to any cellular system.

3D cell mapping↗

Gaussian Mixture Models for Temporal Depth Fusion

Sensing the 3D environment of a moving robot is essential for collision avoidance. Most 3D sensors produce dense depth maps, which are subject to imperfections due to various environmental factors. Temporal fusion of depth maps is crucial to overcome those. Temporal fusion is traditionally done in 3D space with voxel data structures, but it can be approached by temporal fusion in image space, with potential benefits in reduced memory and computational cost for applications like reactive collision avoidance for micro air vehicles. In this paper, we present an efficient Gaussian Mixture Models based depth map fusion approach, introducing an online update scheme for dense representations. The environment is modeled from an ego-centric point of view, where each pixel is represented by a mixture of Gaussian inverse-depth models. Consecutive frames are related to each other by transformations obtained from visual odometry. This approach achieves better accuracy than alternative image space depth map fusion techniques at lower computational cost.

Matthies, Larry↗

Functional brain imaging of a complex navigation task following one night of total sleep deprivation

Study Objectives: To assess the cerebral effects associated with sleep deprivation in a simulation of a complex, real-world, high-risk task. Design and Interventions: A two-week, repeated measures, cross-over experimental protocol, with counterbalanced orders of normal sleep (NS) and total sleep deprivation (TSD). Setting: Each subject underwent functional magnetic resonance imaging (fMRI) while performing a dual-joystick, 3D sensorimotor navigation task (simulated orbital docking). Scanning was performed twice per subject, once following a night of normal sleep (NS), and once following a single night of total sleep deprivation (TSD). Five runs (eight 24s docking trials each) were performed during each scanning session. Participants: Six healthy, young, right-handed volunteers (2 women; mean age 20) participated. Measurements and Results: Behavioral performance on multiple measures was comparable in the two sleep conditions. Neuroimaging results within sleep conditions revealed similar locations of peak activity for NS and TSD, including left sensorimotor cortex, left precuneus (BA 7), and right visual areas (BA 18/19). However, cerebral activation following TSD was substantially larger and exhibited higher amplitude modulations from baseline. When directly comparing NS and TSD, most regions exhibited TSD>NS activity, including multiple prefrontal cortical areas (BA 8/9,44/45,47), lateral parieto-occipital areas (BA 19/39, 40), superior temporal cortex (BA 22), and bilateral thalamus and amygdala. Only left parietal cortex (BA 7) demonstrated NS>TSD activity. Conclusions: The large network of cerebral differences between the two conditions, even with comparable behavioral performance, suggests the possibility of detecting TSD-induced stress via functional brain imaging techniques on complex tasks before stress-induced failures.

Strangman, Gary↗

Numerical Modeling of Ocular Dysfunction in Space

Upon introduction to microgravity, the near-loss of hydrostatic pressure causes a marked cephalic (headward) shift of fluid in an astronaut's body. The fluid shift, along with other factors of spaceflight, induces a cascade of interdependent physiological responses which occur at varying time scales. Long-duration missions carry an increased risk for the development of the Visual Impairment and Intracranial Pressure (VIIP) syndrome, a spectrum of ophthalmic changes including posterior globe flattening, choroidal folds, distension of the optic nerve sheath, kinking of the optic nerve and potentially permanent degradation of visual function. In the cases of VIIP found to date, the initial onset of symptoms occurred after several weeks to several months of spaceflight, by which time the gross bodily fluid distribution is well established. We are developing a suite of numerical models to simulate the effects of fluid shift on the cardiovascular, central nervous and ocular systems. These models calculate the modified mean volumes, flow rates and pressures that are characteristic of the altered quasi-homeostatic state in microgravity, including intracranial and intraocular pressures. The results of the lumped models provide initial and boundary data to a 3D finite element biomechanics simulation of the globe, optic nerve head and retrobulbar subarachnoid space. The integrated set of models will be used to investigate the evolution of the biomechanical stress state in the ocular tissues due to long-term exposure to microgravity.

intraocular pressure↗

Experimental Investigation of Pool Boiling Heat Transfer Enhancement in Microgravity in the Presence of Electric Fields

In boiling high heat fluxes are possible driven by relatively small temperature differences, which make its use increasingly attractive in aerospace applications. The objective of the research is to develop ways to overcome specific problems associated with boiling in the low gravity environment by substituting the buoyancy force with the electric force to enhance bubble removal from the heated surface. Previous studies indicate that in terrestrial applications nucleate boiling heat transfer can be increased by a factor of 50, as compared to values obtained for the same system without electric fields. The goal of our research is to experimentally explore the mechanisms responsible for EHD heat transfer enhancement in boiling in low gravity conditions, by visualizing the temperature distributions in the vicinity of the heated surface and around the bubble during boiling using real-time holographic interferometry (HI) combined with high-speed cinematography. In the first phase of the project the influence of the electric field on a single bubble is investigated. Pool boiling is simulated by injecting a single bubble through a nozzle into the subcooled liquid or into the thermal boundary layer developed along the flat heater surface. Since the exact location of bubble formation is known, the optical equipment can be aligned and focused accurately, which is an essential requirement for precision measurements of bubble shape, size and deformation, as well as the visualization of temperature fields by HI. The size of the bubble and the frequency of bubble departure can be controlled by suitable selection of nozzle diameter and mass flow rate of vapor. In this approach effects due to the presence of the electric field can be separated from effects caused by the temperature gradients in the thermal boundary layer. The influence of the thermal boundary layer can be investigated after activating the heater at a later stage of the research. For the visualization experiments a test cell was developed. All four vertical walls of the test cell are transparent, and they allow transillumination with laser light for visualization experiments by HI. The bottom electrode is a copper cylinder, which is electrically grounded. The copper block is heated with a resistive heater and it is equipped with 6 thermocouples that provide reference temperatures for the measurements with HI. The top electrode is a mesh electrode. Bubbles are injected with a syringe into the test cell through the bottom electrode. The working fluids presently used in the interferometric visualization experiments, water and PF 5052, satisfy requirements regarding thermophysical, optical and electrical properties. A 30kV power supply equipped with a voltmeter allows to apply the electric field to the electrodes during the experiments. The magnitude of the applied voltage can be adjusted either manually or through the LabVIEW data acquisition and control system connected to a PC. Temperatures of the heated block are recorded using type-T thermocouples, whose output is read by a data acquisition system. Images of the bubbles are recorded with 35mm photographic and 16mm high-speed cameras, scanned and analyzed using various software packages. Visualized temperature fields HI allows the visualization of temperature fields in the vicinity of bubbles during boiling in the form of fringes. Typical visualized temperature distributions around the air bubbles injected into the thermal boundary layer in PF5052 are shown. The temperature of the heated surface is 35 C. The temperature difference for a pair of fringes is approximately 0.05 C. The heat flux applied to the bottom surface is moderate, and the fringe patterns are regular. In the image a bubble penetrating the thermal boundary layer is visible. Because of the axial symmetry of the problem, simplified reconstruction techniques can be applied to recover the temperature field. The thermal plume developing above the heated surface for more intensive heating is shown. The temperature distribution in the liquid is clearly 3D, and tomographic techniques have to be applied to recover the temperature distribution in such a physical situation. A sequence of interferometric images showing the temperature distribution around the rising bubble, recorded with a high-speed camera is shown. Again, the temperature distribution is 3D, and a more complex approach to the evaluation, the tomographic reconstruction has to be taken. Measurement of the temperature distribution from the fringe pattern temperature distributions that yield important information regarding heat transfer are determined. Two algorithms that allow the quantitative evaluation of interferometric fringe patterns and the reconstruction of temperature fields during boiling have been developed at the Heat Transfer Laboratory of the Johns Hopkins University. In the first algorithm the bubble is assumed to be axially symmetrical, which significantly reduces the computational effort for quantifying the temperature distribution around the bubble. For this purpose the thermal boundary layer around the bubble is divided into equidistant concentric shells, and the refractive index is assumed to be constant in each of the shells. Since large temperature gradients are expected in the vicinity of the bubble during boiling, the deflection of the light beam cannot be neglected in boiling experiments. Since the exit angle of the light beam is known, this allows to account for the deflections and phase shifts outside the boundary layer (in the bulk fluid and in the windows of the test cell). Three dimensional temperature distributions in the vicinity of the bubble are reconstructed using tomographic techniques. In tomography, the measurement volume is sliced into 2D planes. In the present study these planes are parallel to the heated surface. The objective is to determine the values of the field parameter of interest in form of the field function in these 2D planes. The field parameter is the change of the refractive index of the liquid in the measurement volume caused by temperature changes. By superimposing data for many 2D planes recorded at the same time instant, the 3D temperature distribution in the measurement volume is recovered.

Herman, Cila↗