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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 235 records · Page 13

DNS of Hydrodynamic Instabilities of Laminar H2/O2/N2 Flames at Elevated Pressure

The atypical combustion properties of hydrogen have long provided an interest for hydrogen-enriched combustion, emphasized in recent years by increasingly stringent emission regulations. Significant work has been focused on the small hydrocarbon(C1-C3)/hydrogen blends, but much less is known about the effect of hydrogen on heavier hydrocarbon combustion, of interest for the aviation and automotive industry. In this work, we perform direct numerical simulations (DNS) of spherically expanding laminar n-dodecane/H2 flames in a constant-volume vessel at elevated pressure and a range of hydrogen seeding levels. A low Mach number model is used to represent the gas and flame dynamics allowing for a temporally varying, spatially homogeneous pressure field, while also enabling numerical evolution of the system numerically at time step sizes governed by the advective CFL limit rather than acoustic processes. We use an adaptive mesh refinement (AMR) approach to tackle the large separation of scales associated with high pressure premixed flame surfaces propagating in a laboratory-scale closed domain. We incorporate detailed chemistry and transport models for the reacting flow and focus the analysis on the effects of the pressure rise on the flame propagation characteristics and morphology as the hydrogen content is increased. The presence of fast diffusive H2 and the pressure rise results in dramatic thinning of the flame and the potential onset of hydrodyanmic and theromdiffusive instabilities. We assess the potential role of these instabilities on the ability to accurately measure laminar burning speed experimentally based on the mean flame surface propagation speed.

high pressure↗

Observations of Ocean Primary Productivity Using MODIS

Measuring the magnitude and variability of oceanic net primary productivity (NPP) represents a key advancement toward our understanding of the dynamics of marine ecosystems and the role of the ocean in the global carbon cycle. MODIS observations make two new contributions in addition to continuing the bio-optical time series begun with Orbview-2's SeaWiFS sensor. First, MODIS provides weekly estimates of global ocean net primary productivity on weekly and annual time periods, and annual empirical estimates of carbon export production. Second, MODIS provides additional insight into the spatial and temporal variations in photosynthetic efficiency through the direct measurements of solar-stimulated chlorophyll fluorescence. The two different weekly productivity indexes (first developed by Behrenfeld & Falkowski and by Yoder, Ryan and Howard) are used to derive daily productivity as a function of chlorophyll biomass, incident daily surface irradiance, temperature, euphotic depth, and mixed layer depth. Comparisons between these two estimates using both SeaWiFS and MODIS data show significant model differences in spatial distribution after allowance for the different integration depths. Both estimates are strongly dependence on the accuracy of the chlorophyll determination. In addition, an empirical approach is taken on annual scales to estimate global NPP and export production. Estimates of solar stimulated fluorescence efficiency from chlorophyll have been shown to be inversely related to photosynthetic efficiency by Abbott and co-workers. MODIS provides the first global estimates of oceanic chlorophyll fluorescence, providing an important proof of concept. MODIS observations are revealing spatial patterns of fluorescence efficiency which show expected variations with phytoplankton photo-physiological parameters as measured during in-situ surveys. This has opened the way for research into utilizing this information to improve our understanding of oceanic NPP variability. Deriving the ocean bio-optical properties places severe demands on instrument performance (especially band to band precision) and atmospheric correction. Improvements in MODIS instrument characterization and calibration over the first 16 mission months have greatly improved the accuracy of the chlorophyll input fields and FLH, and therefore the estimates of NPP and fluorescence efficiency. Annual estimates now show the oceanic NPP accounts for 40-50% of the global total NPP, with significant interannual variations related to large scale ocean processes. Spatial variations in ocean NPP, and exported production, have significant effects on exchange of CO2 between the ocean and atmosphere. Further work is underway to improve both the primary productivity model functions, and to refine our understanding of the relationships between fluorescence efficiency and NPP estimates. We expect that the MODIS instruments will prove extremely useful in assessing the time dependencies of oceanic carbon uptake and effects of iron enrichment, within the global carbon cycle.

Esaias, Wayne E.↗

Satellite Remote Sensing of Cirrus: An Overview

The determination of cirrus properties over relatively large spatial and temporal scales will, in most instances, require the use of satellite data. Global coverage, at resolutions as high as several meters are attainable with Landsat, while temporal coverage at 1-min intervals is now available with the latest Geostationary Operational Environmental Satellite (GOES) imagers. Cirrus can be analyzed via interpretation of the radiation that they reflect or emit over a wide range of the electromagnetic spectrum. Many of these spectra and high-resolution satellite data can be used to understand certain aspects of cirrus clouds in particular situations. Production of a global climatology of cirrus clouds, however, requires compromises in spatial, temporal, and spectral coverage. This paper summarizes the state of the art and the potential for future passive remote sensing systems for both understanding cirrus formation and acquiring sufficient statistics to constrain and refine weather and climate models.

Minnis, Patrick↗

Near-field supersonic flow predictions by an adaptive unstructured tetrahedral grid solver

Applicability of a three-dimensional solution adaptive unstructured tetrahedral Euler flow solver about generic models for near-field sonic boom pressure signature predictions is evaluated. Comparisons of computational and experimental data demonstrates the capability of the method for predicting inviscid solutions useful for high speed calculations about simple 3-D geometries. The approach has promising features and results indicate potential for application to more complex configurations. The mesh generation is based on the advancing front technique, and steady state solutions of the Euler equations are achieved by explicit time integration. Spatial discretization uses the Taylor-Galerkin approach; an alternate time integration, based on the Runge-Kutta method, is also included. The solution-adaptive grid procedure is based on either remeshing or mesh refinement techniques. An alternative geometry-adaptive grid procedure has also been incorporated.

Djomehri, M. J.↗

Automatic Calibration and Health Monitoring of Infrastructure Sensors

Smart transportation infrastructure relies on networks of heterogeneous sensors - cameras, radars, and lidars - continuously monitoring traffic conditions. However, executing the initial spatial calibration of multiple sensors and the subsequent health monitoring presents significant operational challenges. Environmental factors, mechanical vibrations, and gradual drift cause spatial misalignment, degrading fusion performance and tracking accuracy. Traditional calibration approaches require manual intervention with specialized targets or survey equipment, resulting in service interruptions and high maintenance costs. This work presents an automated framework for initial calibration and continuous health monitoring without human intervention or service disruption. Our approach addresses two critical problems: (1) detecting when sensors become miscalibrated during operation, and (2) automatically re-establishing spatial alignment using only operational traffic data. The health monitoring component analyzes measurement innovations - differences between sensor observations and predicted object states - to detect systematic biases indicative of calibration drift. By computing bias magnitude, directional consistency, and rejection rates, the system identifies miscalibrations as small as 0.5 meters. Unlike traditional methods requiring known calibration targets, our diagnostic operates continuously on live traffic observations, enabling early detection before fusion quality degrades. The automatic recalibration algorithm leverages overlapping sensor fields-of-view and temporal correlation of vehicle observations. Using graph-based optimization, the system automatically discovers which sensor pairs observe common regions, estimates pairwise spatial transformations using RANSAC-based robust estimation, and jointly optimizes all sensor poses through bundle adjustment. The framework handles practical deployment challenges, including different sensor sampling rates (1-10 Hz), varying installation positions, unknown orientations, and limited overlap regions (>10%). When approximate sensor positions are available from installation surveys (+/-1m accuracy), the algorithm additionally estimates sensor orientations, refining both position and rotation to sub-meter and sub-degree accuracy. We validate the framework on multi-hour traffic datasets from six heterogeneous sensors with sampling rates ranging from 1 Hz to 10 Hz. Results demonstrate successful calibration even with sparse overlap (<20%) and automatic detection of miscalibrations exceeding 0.8 meters. This work enables a "deploy-and-forget" sensor infrastructure that maintains calibration autonomously, reducing maintenance costs while improving tracking accuracy. The techniques generalize beyond transportation to any multi-sensor monitoring application requiring robust spatial alignment, including smart cities, industrial monitoring, and surveillance systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Data-Driven Unit Commitment Refinement - a Scalable Approach for Complex Modern Power Grids

Integration of renewable generation, which is often intermittent and decentralized, substantially increases the stochasticity and complexity of power grid operations. Future power systems planning will require significant computational capability to evaluate balance between demand and supply under varying conditions, both temporally and spatially. The standard approach for generation unit commitment is to use mixed-integer linear programming to find the optimal generation schedule considering ramping and generator constraints. In the future grid this poses computational scalability challenges because generation and demand are not known with certainty due to stochasticity in weather and complexity of the grid. To address this challenge, we present a data-driven unit commitment approach that can efficiently include stochastic weather impacts and contingency considerations to improve unit commitment. Our approach uses graph-based data analytics techniques on solutions to the security constrained (and possibly stochastic) economic dispatch problem to identify potential improvements to a given unit commitment. Recent breakthroughs in fully-parallel stochastic economic dispatch software allow this approach to be scalably deployed. Simulations on synthetic South Carolina and Texas grids show this method can improve grid reliability with security constraints over a set of contingencies, while also meaningfully lowering total generation cost.

Holt, Timothy↗

3D Multiresolution Velocity Model Fusion with Probability Graphical Models

ABSTRACT The variability in spatial resolution of seismic velocity models obtained via tomographic methodologies is attributed to many factors, including inversion strategies, ray-path coverage, and data integrity. Integration of such models, with distinct resolutions, is crucial during the refinement of community models, thereby enhancing the precision of ground-motion simulations. Toward this goal, we introduce the probability graphical model (PGM), combining velocity models with heterogeneous resolutions and nonuniform data point distributions. The PGM integrates data relations across varying resolution subdomains, enhancing detail within low-resolution (LR) domains by utilizing information and prior knowledge from high-resolution (HR) subdomains through a maximum posterior problem. Assessment of efficacy, utilizing both 2D and 3D velocity models—consisting of synthetic checkerboard models and a fault-zone model from Ridgecrest, California—demonstrates noteworthy improvements in accuracy, compared to state-of-the-art fusion techniques. Specifically, we find reductions of 30% and 44% in computed travel-time residuals for 2D and 3D models, respectively, as compared to conventional smoothing techniques. Unlike conventional methods, the PGM’s adaptive weight selection facilitates preserving and learning details from complex, nonuniform HR models and applies the enhancements to the LR background domain.

Geochemistry & Geophysics↗

Quantum mechanical model of crossing and anti-crossing points in 3D full-band Monte Carlo simulations

This work presents a 3D quantum mechanics based model to address the physics at band structure crossing/anti-crossing points in full band Monte Carlo (FBMC) simulations. The model solves the Krieger and Iafrate (KI) equations in real time using pre-computed coefficients at k-points spatially sampled within the first Brillouin zone. Solving the KI equations in real time makes this model applicable for all electric fields, which enables its use in FBMC device simulations. In this work, a two-level refinement scheme is used to aggressively sample regions in proximity to band crossings for accurate solutions to the KI equations and coarsely sample everywhere else to limit the number of k-points used. The presented sampling method is demonstrated on the band structure of silicon but is effective for the band structure of any semiconductor material. Next, the adaptation of the fully quantum KI model into the semi-classical FBMC method is discussed. Finally, FBMC simulations of hole transport in 4H silicon carbide with and without the KI model are performed. Results along different crystallographic directions for a wide range of electric fields are compared to previously published simulation and experimental values.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Parallel Lattice Subpaving Map (plsm)

Custom spatial subdivision of N-dimensional lattice region in GPU memory. An extension of the method of a hyper-octree is used to allow for arbitrary subdivision ratios in each dimension. In addition, the decision to refine (or select) a given sub-region is based on a user-provided callback, allowing for arbitrary refinement domains to be expressed either geometrically or programmatically.

Fackler, Philip↗

Accuracy Enhancement of Nuclear Power Plant Simulators Utilizing High Accuracy Simulation Predictions

More recently, reactor core simulators for core designs associated with commercial nuclear power plants that utilize what is believed to be higher fidelity models have been developed. Features such as neutronics models that utilize transport equation solvers with fine spatial meshes and many energy-groups, thermal-hydraulic models that utilize sub-channel solvers with fine spatial mesh and capable of treating a wide range of fluid conditions, and fuel-coolant chemistry interaction models capable of treating CRUD deposition are to be found in these higher fidelity core simulators. These reactor core simulators require access to higher performance computers, characterized by many processors, cores and large memory. So associated with utilization of these simulators is access to high performance computers and ability to accommodate in one’s workflow longer execution times. By contrast, currently used core simulators by the nuclear industry can execute on engineering workstations and have execution times of seconds to minutes. The desirability for having short execution times is not only desired for support of time critical tasks but supports the mental process of decision making by engineers. The goal of the work reported upon here has the objective of retaining the fidelity of higher fidelity models while retaining the ability to utilize engineering workstations. Beyond the core simulator goal, additional goals of this work include incorporating the just described core simulator capability into a Nuclear Steam Supply System (NSSS) simulator, and to incorporate the resulting capability into an environment supportive of design and operational decision making associated with nuclear power stations. The model selected for the core neutronics model is the NESTLE code, for the core thermal-hydraulic model is the CTF code utilizing coarse mesh, and for the NSSS model is the RELAP5-3D code. WSC’s proprietary 3KEYMASTERTM platform is being used to provide software coupling, user interface, visualization, and reporting. The NESTLE core neutronics simulator was first integrated with the CTF core thermal-hydraulic simulator using CTF developed communication commands which are also used for CTF to communicate with RELAP5-3D under WSC’s proprietary 3KEYMASTERTM platform. To assure NESTLE prediction consistency with higher fidelity core neutronic simulators, buffer codes have been created to automatically generate from output files written by the VERA core simulator the NESTLE nodal neutronic parameter’ library, geometry, and pin-power reconstruction input files, thereby avoiding a number of challenges associated with utilizing lattice physics codes and providing consistency with VERA predictions. To treat absorber rod effects a multi-set library is utilized, where a set refers to a specific absorber rod fully inserted pattern. A coarse spatial mesh CTF model was developed with features added that support using CTF as envisioned in the engineering quality simulator. A hybrid meshing approach was implemented to allow for automated construction of models with mixed levels of refinement. Specifically, a core model could resolve some assemblies at a nodal level (4 subchannels per assembly) and others at a pin-resolution (one subchannel per coolant subchannel in the assembly). The intention is that this will allow for better resolution of limiting conditions such as DNBR and PCT, which are based on local rod and subchannel conditions. Further development was done of features that enhance the capabilities for the envisioned engineering quality simulator that has been developed, but now for RELAP-3D. The RELAP5-3D code development includes ability to model more than 999 components and the addition of the cross-channels turbulence mixing model and the void drift model that are implemented in CTF, aiming to achieve closer prediction agreement of the two codes for transient simulations, specifically, more accurate matches of the overall mass, momentum, and energy exchanges of both the liquid and gas phases between the neighboring core assemblies. Graphics were also developed for the Instructor Station for this project under WSC’s proprietary 3KEYMASTERTM platform to facilitate design and operational decision making.

42 ENGINEERING↗

Development of Numerical Extended Hydrodynamics for Transition-Regime Non-Equilibrium Flows Encountered in Semiconductor Manufacturing Processes

Six months of funding was received for the proposed three year research program (funding for the period from March 1, 1997 to August 31, 1997). Although the official starting date for the project was March 1, 1997, no funding for the project was received until July 1997. In the funded research period, considerable progress was made on Phase I of the proposed research program. The initial research efforts concentrated on applying the 10-, 20-, and 35-moment Gaussian-based closures to a series of standard two-dimensional non-reacting single species test flow problems, such as the flat plate, couette, channel, and rearward facing step flows, and to some other two-dimensional flows having geometries similar to those encountered in chemical-vapor deposition (CVD) reactors. Eigensystem analyses for these systems for the case of two spatial dimensions was carried out and efficient formulations of approximate Riemann solvers have been formulated using these eigenstructures. Formulations to include rotational non-equilibrium effects into the moment closure models for the treatment of polyatomic gases were explored, as the original formulations of the closure models were developed strictly for gases composed of monatomic molecules. The development of a software library and computer code for solving relaxing hyperbolic systems in two spatial dimensions of the type arising from the closure models was also initiated. The software makes use of high-resolution upwind finite-volumes schemes, multi-stage point implicit time stepping, and automatic adaptive mesh refinement (AMR) to solve the governing conservation equations for the moment closures. The initial phase of the code development was completed and a numerical investigation of the solutions of the 10-moment closure model for the simple two-dimensional test cases mentioned above was initiated. Predictions of the 10-moment model were compared to available theoretical solutions and the results of direct-simulation Monte Carlo (DSMC) calculations. The first results of this study were presented at a meeting last year.

Groth, Clinton P. T.↗

Remote Sensing of In-Flight Icing Conditions: Operational, Meteorological, and Technological Considerations

Remote-sensing systems that map aircraft icing conditions in the flight path from airports or aircraft would allow icing to be avoided and exited. Icing remote-sensing system development requires consideration of the operational environment, the meteorological environment, and the technology available. Operationally, pilots need unambiguous cockpit icing displays for risk management decision-making. Human factors, aircraft integration, integration of remotely sensed icing information into the weather system infrastructures, and avoid-and-exit issues need resolution. Cost, maintenance, power, weight, and space concern manufacturers, operators, and regulators. An icing remote-sensing system detects cloud and precipitation liquid water, drop size, and temperature. An algorithm is needed to convert these conditions into icing potential estimates for cockpit display. Specification development requires that magnitudes of cloud microphysical conditions and their spatial and temporal variability be understood at multiple scales. The core of an icing remote-sensing system is the technology that senses icing microphysical conditions. Radar and microwave radiometers penetrate clouds and can estimate liquid water and drop size. Retrieval development is needed; differential attenuation and neural network assessment of multiple-band radar returns are most promising to date. Airport-based radar or radiometers are the most viable near-term technologies. A radiometer that profiles cloud liquid water, and experimental techniques to use radiometers horizontally, are promising. The most critical operational research needs are to assess cockpit and aircraft system integration, develop avoid-and-exit protocols, assess human factors, and integrate remote-sensing information into weather and air traffic control infrastructures. Improved spatial characterization of cloud and precipitation liquid-water content, drop-size spectra, and temperature are needed, as well as an algorithm to convert sensed conditions into a measure of icing potential. Technology development also requires refinement of inversion techniques. These goals can be accomplished with collaboration among federal agencies including NASA, the FAA, the National Center for Atmospheric Research, NOAA, and the Department of Defense. This report reviews operational, meteorological, and technological considerations in developing the capability to remotely map in-flight icing conditions from the ground and from the air.

Ryerson, Charles C.↗

Parallel Adaptive High-Order CFD Simulations Characterizing Cavity Acoustics for the Complete SOFIA Aircraft

This paper presents one-of-a-kind MPI-parallel computational fluid dynamics simulations for the Stratospheric Observatory for Infrared Astronomy (SOFIA). SOFIA is an airborne, 2.5-meter infrared telescope mounted in an open cavity in the aft of a Boeing 747SP. These simulations focus on how the unsteady flow field inside and over the cavity interferes with the optical path and mounting of the telescope. A temporally fourth-order Runge-Kutta, and spatially fifth-order WENO-5Z scheme was used to perform implicit large eddy simulations. An immersed boundary method provides automated gridding for complex geometries and natural coupling to a block-structured Cartesian adaptive mesh refinement framework. Strong scaling studies using NASA's Pleiades supercomputer with up to 32,000 cores and 4 billion cells shows excellent scaling. Dynamic load balancing based on execution time on individual AMR blocks addresses irregularities caused by the highly complex geometry. Limits to scaling beyond 32K cores are identified, and targeted code optimizations are discussed.

Acoustics↗

Understanding Organics in Meteorites and the Pre-Biotic Environment

(1) Refinement of the analytic capabilities of our experiment via characterization of molecule-specific response and the effects upon analysis of the type of sample under investigation; (2) Measurement of polycyclic aromatic hydrocarbons (PAHs) with high sensitivity and spatial resolution within extraterrestrial samples; (3) Investigation of the interstellar reactions of PAHs via the analysis of species formed in systems modeling dust grains and ices; (4) Investigations into the potential role of PAHs in prebiotic and early biotic chemistry via photoreactions of PAHs under simulated prebiotic Earth conditions. To meet these objectives, we use microprobe laser-desorption, laser-ionization mass spectrometry (MuL(exp 2)MS), which is a sensitive, selective, and spatially resolved technique for detection of aromatic compounds. Appendix A presents a description of the MuL(exp 2)MS technique. The initial grant proposal was for a three-year funding period, while the award was given for a one-year interim period. Because of this change in time period, emphasis was shifted from the first research goal, which was more development-oriented, in order to focus more on the other analysis-oriented goals. The progress made on each of the four research areas is given below.

Zare, Richard N.↗

Geospatial Method for Computing Supplemental Multi-Decadal U.S. Coastal Land-Use and Land-Cover Classification Products, Using Landsat Data and C-CAP Products

This paper discusses the development and implementation of a geospatial data processing method and multi-decadal Landsat time series for computing general coastal U.S. land-use and land-cover (LULC) classifications and change products consisting of seven classes (water, barren, upland herbaceous, non-woody wetland, woody upland, woody wetland, and urban). Use of this approach extends the observational period of the NOAA-generated Coastal Change and Analysis Program (C-CAP) products by almost two decades, assuming the availability of one cloud free Landsat scene from any season for each targeted year. The Mobile Bay region in Alabama was used as a study area to develop, demonstrate, and validate the method that was applied to derive LULC products for nine dates at approximate five year intervals across a 34-year time span, using single dates of data for each classification in which forests were either leaf-on, leaf-off, or mixed senescent conditions. Classifications were computed and refined using decision rules in conjunction with unsupervised classification of Landsat data and C-CAP value-added products. Each classification's overall accuracy was assessed by comparing stratified random locations to available reference data, including higher spatial resolution satellite and aerial imagery, field survey data, and raw Landsat RGBs. Overall classification accuracies ranged from 83 to 91% with overall Kappa statistics ranging from 0.78 to 0.89. The accuracies are comparable to those from similar, generalized LULC products derived from C-CAP data. The Landsat MSS-based LULC product accuracies are similar to those from Landsat TM or ETM+ data. Accurate classifications were computed for all nine dates, yielding effective results regardless of season. This classification method yielded products that were used to compute LULC change products via additive GIS overlay techniques.

Spruce, J. P.↗

Effect of Geometric Granularity on the Noise Signature of a Full-Scale Large Civil Transport Nose Landing Gear

Results from a comprehensive simulation campaign focused on characterizing the air-frame noise signature of a full-scale Boeing 777-300ER nose landing gear are presented. The as-flown, installed nose gear geometry was used to assess how accurately the selected computational methodology can predict far-field noise before extending the simulation approach to the complete B777-300ER aircraft in landing configuration. To facilitate direct comparisons with experimental data, the simulations were conducted for conditions matching those recorded for a flyby of the same aircraft over the ground-based phased microphone array used during the 2005 Quiet Technology Demonstrator II test. The far-field acoustic footprint of the nose landing gear was computed via a Ffowcs-Williams and Hawkings integral approach, with pressures on the model solid surface or flow quantities on a permeable data surface enclosing the gear used as input. A grid refinement study performed for the baseline gear con-figuration to establish the convergence behavior of the far-field spectrum indicated that the sound pressure levels had converged at frequencies slightly beyond 5 kHz for the finest spatial resolution attempted. To ascertain the effects of geometric granularity on far-field noise, simulations of a defeatured version of the nose gear were undertaken. Comparisons with fully-dressed gear results indicated that finer geometric details add 2–4 dB to the sound pressure levels at mid- to high-frequencies (800 Hz to 5 kHz), suggesting that for accurate noise prediction such details cannot be neglected.

airframe noise↗

AIRS Point Spread Function Reconstruction using AIRS and MODIS Data

The purpose of this work is to use data from the Atmospheric Infrared Sounder (AIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) to refine our knowledge of post-launch AIRS point spread functions (PSFs), including suspected changes over the mission. We develop methodology, by deriving mathematical optimization formulation based on variational principles and Sobolev gradient descent, for reconstruction of AIRS spatial response functions. We use the data over the ocean, collected for the duration of a day, to reconstruct a single PSF. We examine the repeatability of our reconstructions by computing PSFs based on data collected during two consecutive days, and also investigating the change in the reconstructions by comparing the reconstructed PSF based on data collected in the beginning and the middle of the mission. We also quantify uncertainties in our reconstruction results.

Vese, Luminita↗

Ray-tracing image simulations of transparent objects with complex shape and inhomogeneous refractive index

Optical images of transparent three-dimensional objects can be different from a replica of the object’s cross section in the image plane, due to refraction at the surface or in the body of the object. Simulations of the object’s image are thus needed for the visualization and validation of physical models. We report ray tracing image simulations that achieved high physical fidelity, reproducing optical behaviors and image features not rendered in previous studies. We replicated brightfield microscopy images of drops with complex shapes, and images of pressure and shock waves traveling inside them. For high physical fidelity, the simulations must replicate the spatial and angular distribution of illumination rays, and both the experiment and the simulation must be designed for accurate optical modeling. The simulations are highly sensitive to the properties of the drops and can be used to diagnose and refine fluid dynamics models. The simulated images can also be optimized to extract multiple 3D properties from experimental images. Compared to specialized single-shot 3D imaging methods, this approach has the advantage that it preserves the experimental simplicity, the high resolution, and the visual interpretability characteristic to basic optical imaging. The techniques introduced here are directly applicable to optical microscopy, so they can be used in other fields, such as microfluidics and biology, to expand the type and the accuracy of three-dimensional information that can be extracted from basic optical images.

Cavitation↗