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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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Principle heat absorption of silica-reinforced plastic ablative materials occurs from the in-depth reaction of silica with carbon to form silicon monoxide and carbon monoxide. The higher the degree of completion of this reaction, the higher the capacity of the ablative material to absorb heat.
The technique of modulation, or variable coefficients, is discussed and the analytical formulation is reviewed. Representative numerical results of the use of modulation are shown for the lifting and nonlifting cases. These results include the effects of modulation on peak acceleration, entry corridor, and heat absorption. Results are given for entry at satellite speed and escape speed. The indications are that coefficient modulation on a vehicle with good lifting capability offers the possibility of sizable loading reductions or, alternatively, wider corridors; thus, steep entries become practical from the loading standpoint. The amount of steepness depends on the acceptable heating penalty. The price of sizable fractions of the possible gains does not appear to be excessive.
Solar radiation is the primary source of energy driving atmospheric and oceanic circulations. Concerned with the huge computing time required for computing radiative transfer in weather and climate models, solar heating in minor absorption bands has often been neglected. The individual contributions of these minor bands to the atmospheric heating is small, but collectively they are not negligible. The solar heating in minor bands includes the absorption due to water vapor in the photosynthetically active radiation (PAR) spectral region from 14284/cm to 25000/cm, the ozone absorption and Rayleigh scattering in the near infrared, as well as the O2 and CO2 absorption in a number of weak bands. Detailed high spectral- and angular-resolution calculations show that the total effect of these minor absorption is to enhance the atmospheric solar heating by approximately 10%. Depending upon the strength of the absorption and the overlapping among gaseous absorption, different approaches are applied to parameterize these minor absorption. The parameterizations are accurate and require little extra time for computing radiative fluxes. They have been efficiently implemented in the various atmospheric models at NASA/Goddard Space Flight Center, including cloud ensemble, mesoscale, and climate models.
A simple parameterization of ozone absorption in the 9.6-micron region which is suitable for two- and three-dimensional stratospheric and tropospheric models is presented. The band is divided into two parts, a brand center region and a band wing region, grouping together regions for which the temperature dependence of absorption is similar. Each of the two regions is modeled with a function having the form of the Goody random model, with pressure and temperature dependent band parameters chosen by empirically fitting line-by-line equivalent widths for pressures between 0.25 and 1000 mbar and ozone absorber amounts between 1.0 x 10 to the -7th and 1.0 cm atm. The model has been applied to calculations of atmospheric heating rates using an absorber amount weighted mean pressure and temperature along the inhomogeneous paths necessary for flux computations. In the stratosphere, maximum errors in the heating rates relative to line-by-line calculations are 0.1 K/d, or 5 percent of the peak cooling at the stratopause. In the troposphere the errors are at most 0.005 K/d.
A capacitance/dielectric sensor was designed, constructed, and used to measure in real time the in-situ water concentration in a desiccant water bed. Measurements were carried out with two experimental setups: (1) passing nitrogen through a humidity generator and allowing the gas stream to become saturated at a measured temperature and pressure, and (2) injecting water via a syringe pump into a nitrogen stream. Both water vapor generating devices were attached to a downstream vertically-mounted water capture bed filled with 19.5 g of Moisture Gone desiccant. The sensor consisted of two electrodes: (1) a 1/8" dia stainless steel rod placed in the middle of the bed and (2) the outer shell of the stainless steel bed concentric with the rod. All phases of the water capture process (background, heating, absorption, desorption, and cooling) were monitored with capacitance. The measured capacitance was found to vary linearly with the water content in the bed at frequencies above 100 kHz indicating dipolar motion dominated the signal; below this frequency, ionic motion caused nonlinearities in the water concentration/capacitance relationship. The desiccant exhibited a dielectric relaxation whose activation energy was lowered upon addition of water indicating either a less hindered rotational motion or crystal reorientation.
Three model configurations are presented for multi-step time series predictions of the heat absorbed by the water and steam in a thermal power plant. The models predict over horizons of 2, 4, and 6 steps into the future, where each step is a 5-minute increment. The evaluated models are a pure machine learning model, a novel hybrid machine learning and physics-based model, and the hybrid model with an incomplete dataset. The hybrid model deconstructs the machine learning into individual boiler heat absorption units: economizer, water wall, superheater, and reheater. Each configuration uses a gated recurrent unit (GRU) or a GRU-based encoder–decoder as the deep learning architecture. Mean squared error is used to evaluate the models compared to target values. The encoder–decoder architecture is over 11% more accurate than the GRU only models. The hybrid model with the incomplete dataset highlights the importance of the manipulated variables to the system. The hybrid model, compared to the pure machine learning model, is over 10% more accurate on average over 20 iterations of each model. Automatic differentiation is applied to the hybrid model to perform a local sensitivity analysis to identify the most impactful of the 72 manipulated variables on the heat absorbed in the boiler. The models and sensitivity analyses are used in a discussion about optimizing the thermal power plant.
Here, the development of advanced processes for carbon dioxide capture requires reliable thermodynamic models to ensure accurate process design. This work presents an optimized parameter set of the Extended UNIQUAC model for advanced mixed solvent solutions containing CO 2 -MDEA-NH 3 -K 2 CO 3 in water. The model was parameterized using vapor–liquid equilibrium, pure component saturation pressure, excess enthalpy, heat of absorption, molar heat capacity, apparent molar heat capacity, and solid–liquid equilibrium. These thermal and equilibrium properties cover temperatures between 253.6 K to 600 K and pressures up to 75.6 bar. The current model represents an extension of previous versions that were suitable for modeling aqueous NH 3 and K 2 CO 3 solutions. This parametrization accounts for molecular interactions between MDEA and these two components, which allows for the design of advanced capture processes. This paper demonstrates that the new model parameters are valid within the range of operational conditions typically found in CO 2 capture processes.
An analytical and experimental investigation of air-cooled condensers for small-scale ammonia-water absorption heat pumps is presented. Conventional round-tube corrugated fin design and a novel multi-pass tube array design are considered for a condenser operating at severe ambient conditions within a compact footprint. Segmental heat and mass transfer models are developed to gain a deeper understanding of the characteristics of each design. Predicted heat duties are within 5% of the measured values. The limitations of correlations to predict air-side pressure drop in corrugated fins are identified. The performance of the novel multi-pass tube array condenser was comparable to that of conventional condensers, but is determined to be air-side limited throughout length of the heat exchanger. An improved multi-pass condenser design with fins for increased air-side area is proposed using the insights gained from the modeling and experiments. In closing this design meets the heat duty requirements at severe ambient conditions, while decreasing the size of the heat exchanger by 33%.
Accurate estimation of convective boundary layer height (CBLH) is vital for weather, climate, and air quality modeling. Machine learning (ML) shows promise in CBLH prediction, but input parameter selection often lacks physical grounding, limiting generalizability. This study introduces a novel ML framework for CBLH prediction, integrating thermodynamic constraints and the diurnal CBLH cycle as an implicit physical guide. Boundary layer growth is modeled as driven by surface heat fluxes and atmospheric heat absorption represented with the low tropospheric stability, using the diurnal cycle as input and output. TPOT and AutoKeras are employed to select optimal models, validated against Doppler lidar-derived CBLH data, achieving an R 2 of 0.84 across untrained years. Comparisons of eddy covariance (ECOR) and energy balance Bowen ratio (EBBR) flux measurements show the same prediction capability. Models trained on the ARM SGP C1 site with ECOR data and tested at E37 and E39 yield R 2 values of 0.79 and 0.81, respectively, demonstrating their adaptability. The ML model trained with all sites' data slightly enhances the performance compared with ML models trained over single-site data. The interquartile range for predicted CBLH is consistently narrower than that for DL-derived CBLH, reflecting lower variability in predicted CBLH compared to DL-derived CBLH, which is influenced by additional factors, which are not well represented with the model inputs. The model's generalizability across multiple sites at the ARM SGP site demonstrates its potential for transfer to greater distances, offering a scalable approach for enhancing boundary layer parameterization in atmospheric models.
Lunar thermal emission interpretation for solar heat absorption and conduction as indication of surface structure
Self focusing of CW argon laser beam due to absorptive heating in crown glass, emphasizing time dependence of beam diameter as function of distance
Heat absorption and emission balance for thermal control system of spacecraft
Specific heat, absorptance, and emittance of thermal control coatings determined simultaneously by cyclic radiation technique
One of the most vital life support systems is that used to provide the astronaut with an adequate thermal environment. State-of-the-art techniques are reviewed for collecting and rejecting excess heat loads from the suited astronaut. Emphasis is placed on problem areas which exist and which may be suitable topics for university research. Areas covered include thermal control requirements and restrictions, methods of heat absorption and rejection or storage, and comparison between existing methods and possible future techniques.
This paper describes the application of the SINDA (systems improved numerical differencing analyzer) computer program to simulate the operation of the NASA/JSC MIUS integration and subsystems test (MIST) laboratory. The MIST laboratory is designed to test the integration capability of the following subsystems of a modular integrated utility system (MIUS): (1) electric power generation, (2) space heating and cooling, (3) solid waste disposal, (4) potable water supply, and (5) waste water treatment. The SINDA/MIST computer model is designed to simulate the response of these subsystems to externally impressed loads. The computer model determines the amount of recovered waste heat from the prime mover exhaust, water jacket and oil/aftercooler and from the incinerator. This recovered waste heat is used in the model to heat potable water, for space heating, absorption air conditioning, waste water sterilization, and to provide for thermal storage. The details of the thermal and fluid simulation of MIST including the system configuration, modes of operation modeled, SINDA model characteristics and the results of several analyses are described.
System maintains precise thermal control of heat producing component, is not affected by changes in external pressure, ambient thermal environment, or gravity, and operates in both static and spinning attitudes. Size of device's spin axis-oriented orifice determines container pressure which establishes boiling temperature of heat absorption medium.
The equilibrium diagram for the KHF2-H2O system was constructed from cooling and heating curves for the compositions between 5 wt% and 40 wt% KHF2 and the results are shown. The phase diagrams shown is typical of that of a two component system with miscible liquid phases and whole solid phases consist of pure components. A eutectic point was found at approximately 15% KHF2 which remains completely liquid down to a temperature of -9.0 C. No hydrate formation was observed and no anomalous behavior such as the occurrence of solid transitions or metastable states was observed. The effect of rapid freezing on the equilibrium diagram did not appear, and cooling curves exhibited only one halt. Also, at rapid freezing rates, the supercooling of the solutions was smaller than those observed at the slow cooling rates. The existence of a eutectic composition and the slow rate of dissolution of the salt are used to interpret heat absorption behavior in practical applications of the KHF2-H2O system.
A numerical model simulating a variable thickness sea ice cover over a seasonal cycle is presented. The model includes a fixed depth mixed-layer formulation with open water heat absorption and lateral melting terms, and a mechanical distribution function consistent with the physics of the ridging process. The equibrium simulation results in realistic geographical ice thickness variations of April ice along the Canadian Archipelago which exceed 7 m, and thicknesses of about 2 m along the Alaskan North Slope. Ice velocity fields were realistic in shape but 25% larger than the net ice station drift over a year; sensitivity simulations indicated a reduced average annual ice export rate of 0.04 Sv as compared to 0.09 Sv for the equilibrium simulation.