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Predictions from GLIMPS and HFAST design codes are compared with experimental data for the RE-1000 and SPRE free piston Stirling engines. Engine performance and available power loss predictions are compared. Differences exist between GLIMPS and HFAST loss predictions. Both codes require engine specific calibration to bring predictions and experimental data into agreement.
Predictions from GLIMPS and HFAST design codes are compared with experimental data for the RE-1000 and SPRE free piston Stirling engines. Engine performance and available power loss predictions are compared. Differences exist between GLIMPS and HFAST loss predictions. Both codes require engine specific calibration to bring predictions and experimental data into agreement.
Abstract Genome engineering for materials synthesis is a promising avenue for manufacturing materials with unique properties under ambient conditions. Biomineralization in diatoms, unicellular algae that use silica to construct micron-scale cell walls with nanoscale features, is an attractive candidate for functional synthesis of materials for applications including photonics, sensing, filtration, and drug delivery. Therefore, controllably modifying diatom structure through targeted genetic modifications for these applications is a very promising field. In this work, we used gene knockdown in Thalassiosira pseudonana diatoms to create modified strains with changes to structural morphology and linked genotype to phenotype using supervised machine learning. An artificial neural network (NN) was developed to distinguish wild and modified diatoms based on the SEM images of frustules exhibiting phenotypic changes caused by a specific protein (Thaps3_21880), resulting in 94% detection accuracy. Class activation maps visualized physical changes that allowed the NNs to separate diatom strains, subsequently establishing a specific gene that controls pores. A further NN was created to batch process image data, automatically recognize pores, and extract pore-related parameters. Class interrelationship of the extracted paraments was visualized using a multivariate data visualization tool, called CrossVis, and allowed to directly link changes in morphological diatom phenotype of pore size and distribution with changes in the genotype.
In support of efforts to develop improved models of turbulent spray behavior and combustion in diesel engines, experimental data and analysis must be obtained for guidance and validation. For Reynolds-averaged Navier–Stokes (RANS)-based Computational fluid dynamics (CFD) modeling approaches, representative ensemble average experimental results are important. For high-fidelity models such as large eddy simulations (LES)-based CFD, precise individual experimental results are desirable. However, making comparisons between a given experiment and LES is a challenge since local parameters cannot be directly compared. In this work, an optically accessible constant pressure flow rig (CPFR) is utilized to acquire diesel-like fuel injection and reaction behavior simultaneously with three optical diagnostic techniques: rainbow Schlieren deflectometry (RSD), OH* chemiluminescence (OH*), and two-color pyrometry (2CP). The CPFR allows a large number of repeated injection experiments to be performed for statistical analysis and convergence using ensemble-averaging techniques, while maintaining highly repeatable test conditions. Even for stable test conditions, variations in local turbulent fuel–air mixing introduce variability, which manifests as significant differences in OH* and 2CP results. Experimental measurements of characteristic parameters including liquid and vapor jet penetration, liftoff length, soot temperature and concentration, and turbulent flame speed, along with the shot-to-shot variability of each dataset, are presented and discussed. Finally, a statistical method is utilized to analyze the extent of this variability, and to identify superlative injections within the dataset for discussion and analysis of shot-to-shot variations.
A novel and modern framework for energy modeling is developed in this paper with a focus on nuclear energy modeling and simulation. The framework combines multiphysics simulations and real data, with validation by uncertainty quantification tasks and facilitation by machine and deep learning methods. The hybrid framework is built on the basis of a wide range of physical models, real data, mathematical and statistical methods, and artificial intelligence techniques. The framework is demonstrated in different applications, including quantifying uncertainties in computer simulations, multiphysics coupling, analysis of variance using machine learning surrogate models, deep learning of time series phenomena, and propagating parametric uncertainties of nuclear data. The applications demonstrated are oriented to nuclear engineering simulations, even though majority of the methods are applicable to other energy sources (eg, renewable). Efficient utilization of this framework is expected to yield a much better understanding of the physical phenomena analyzed as well as an improvement in the performance of the energy design/model under construction.
Oleaginous yeasts are a promising candidate for the sustainable conversion of lignocellulosic feedstocks into fuels and chemicals, but their growth on these substrates can be inhibited as a result of upstream pretreatment and enzymatic hydrolysis conditions. Previous studies indicate a high citrate buffer concentration during hydrolysis inhibits downstream cell growth and ethanol fermentation in Saccharomyces cerevisiae . In this study, an engineered Rhodosporidium toruloides strain with enhanced lipid accumulation was grown on sorghum hydrolysate with high and low citrate buffer concentrations. Both hydrolysis conditions resulted in similar sugar recovery rates and concentrations. No significant differences in cell growth, sugar utilization rates, or lipid production rates were observed between the two citrate buffer conditions during batch fermentation of R. toruloides . Under fed-batch growth on low-citrate hydrolysate a lipid titer of 16.7 g/L was obtained. Citrate buffer was not found to inhibit growth or lipid production in this engineered R. toruloides strain, nor did reducing the citrate buffer concentration negatively affect sugar yields in the hydrolysate. As this process is scaled-up, $131 per ton of hydrothermally pretreated biomass can be saved by use of the lower citrate buffer concentration during enzymatic hydrolysis.
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The present program focuses on rice because of its importance world-wide as a food. Specifically, the focus is on rice fields in the Philippines. Two primary program objectives are: (1) to establish the feasibility of extracting from ERTS imagery the areas where rice is grown, and (2) to determine those measurements on the imagery which enable the assessment of crop condition. Achieving these objectives with procedures which can be cost-effective can lead the way toward yield prediction, irrigation system management, and similar functions which are known to be important needs in Southeast Asia.
The author has identified the following significant results. Rice is an important food worldwide. Worthwhile goals, particularly for developing nations, are the capability to recognize from satellite imagery: (1) areas where rice is grown, and (2) growth status (irrigation, vigor, yield). A two-step procedure to achieve this is being investigated. Ground truth, and ERTS-1 imagery (four passes) covering 80% of a rice growth cycle for some Philippine sites, have been analyzed. One-D and three-D signature extraction, and synthesis of an initial site recognition/status algorithm have been performed. Results are encouraging. but additional passes and sites must be analyzed. Good position information for extracted data is a must.
Aerodynamic characteristics obtained in a helical flow environment utilizing a rotary balance located in the Langley spin tunnel are presented in plotted form. The configurations tested included the basic airplane, various control deflections, two canard locations, and wing leading edge modifications, as well as airplane components.
Using the ANSYS finite element program, a global model of the aft skirt and a detailed nonlinear model of the failure region was made. The analysis confirmed the area of failure in both STA-2B and STA-3 tests as the forging heat affected zone (HAZ) at the aft ring centerline. The highest hoop strain in the HAZ occurs in this area. However, the analysis does not predict failure as defined by ultimate elongation of the material equal to 3.5 percent total strain. The analysis correlates well with the strain gage data from both the Wyle influence test of the original design aft sjirt and the STA-3 test of the redesigned aft skirt. it is suggested that the sensitivity of the failure area material strength and stress/strain state to material properties and therefore to small manufacturing or processing variables is the most likely cause of failure below the expected material ultimate properties.
In-flight facility data acquisition, distribution, and recording on the NASA Ames Research Center (ARC) DC-8 are performed by the Data Acquisition and Distribution System (DADS). Navigational and environmental data collected by the DADS are converted to engineering units and distributed real-time to investigator stations once per second. Selected engineering units data are printed and displayed on closed circuit television monitors throughout flights. An in-flight graphical display of the DC-8 flight track (with barbs indicating wind direction and magnitude) has recently been added to the DADS capabilities. Logging of data run starts/stops and commentary from the mission director are also provided. All data are recorded to hard disk in-flight and archived to tape medium post-flight. Post-flight, hard copies of the track map and mission director's log are created by the DADS. The DADS is a distributed system consisting of a data subsystem, an Avionic Serial Data-to-VMEbus (ASD2VME) subsystem, and a host subsystem. Each subsystem has a dedicated central processing unit (CPU) and is capable of stand-alone operation. All three subsystems are housed in a single 20-slot VME chassis and communicate with each other over the VMEbus. The data and host subsystems are briefly discussed, and the DC-8 DADS internal configuration and system block diagram are presented.
This compilation of the outstanding characteristics of the available aircraft engines of the world was prepared as a compact ready reference for desk use. It does not pretend to be anything but a skeleton outline of the characteristics of engines reported in the technical press as being in either the experimental, development, or production stage.
An investigation was made to determine the effect of variations in the horizontal and vertical air-entry angles on the performance characteristics of a single-cylinder 2-stroke-cycle compression-ignition test engine. Performance data were obtained over a wide range of engine speed, scavenging pressure, fuel quantity, and injection advance angle with the optimum guide vanes. Friction and blower-power curves are included for calculating the indicated and net performances. The optimum horizontal air-entry angle was found to be 60 degrees from the radial and the optimum vertical angle to be zero, under which conditions a maximum power output of 77 gross brake horsepower for a specific fuel consumption of 0.52 pound per brake horsepower-hour was obtained at 1,800 r.p.m. and 16-1/2 inches of Hg scavenging pressure. The corresponding specific output was 0.65 gross brake horsepower per cubic inch of piston displacement. Tests revealed that the optimum scavenging pressure increased linearly with engine speed. The brake mean effective pressure increased uniformly with air quantity per cycle for any given vane angle and was independent of engine speed and scavenging pressure.
NASA, in collaboration with other US federal agencies, engine/airframe manufacturers, airlines, and airport authorities, recently sponsored a series of 3 ground-based field investigations to examine the particle and gas emissions from a variety of in-use commercial aircraft. Emissions parameters were measured at multiple engine power settings, ranging from idle to maximum thrust, in samples collected at 3 different down stream locations of the exhaust. Sampling rakes at nominally 1 meter down stream contained multiple probes to facilitate a study of the spatial variation of emissions across the engine exhaust plane. Emission indices measured at 1 m were in good agreement with the engine certification data as well as predictions provided by the engine company. However at low power settings, trace species emissions were observed to be highly dependent on ambient conditions and engine temperature.
Disk Recording System (DRS) is a systems-integration computer program for a direct-to-disk (DTD) high-speed data acquisition system (HDAS) that records rocket-engine test data. The HDAS consists partly of equipment originally designed for recording the data on tapes. The tape recorders were replaced with hard-disk drives, necessitating the development of DRS to provide an operating environment that ties two computers, a set of five DTD recorders, and signal-processing circuits from the original tape-recording version of the HDAS into one working system. DRS includes three subsystems: (1) one that generates a graphical user interface (GUI), on one of the computers, that serves as a main control panel; (2) one that generates a GUI, on the other computer, that serves as a remote control panel; and (3) a data-processing subsystem that performs tasks on the DTD recorders according to instructions sent from the main control panel. The software affords capabilities for dynamic configuration to record single or multiple channels from a remote source, remote starting and stopping of the recorders, indexing to prevent overwriting of data, and production of filtered frequency data from an original time-series data file.