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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Impact of Energy Gain and Subsystem Characteristics on Fusion Propulsion Performance Balances

Rapid transportation of large payloads and human crews to destinations throughout the solar system will require propulsion systems having not only very high exhaust velocities (I (sub sp) greater than or equal to 10 (exp 4) to 10 (exp 5) sec) but also extremely low mass-power ratios (alpha less than or equal to 10 (exp -1) kg/kW). Such low a are difficult to achieve with power-limited propulsion systems. but may be attainable with fusion and other high I (sub SP) nuclear concepts that produce energy within the propellant. The magnitude of this energy gain is of fundamental importance. It must be large enough to sustain the nuclear process while still providing a high jet power relative to the massive power-intensive subsystems associated with these types of concepts. This paper evaluates the energy gain and mass-power characteristics required for a consistent with 1-year roundtrip planetary missions ranging up to 100 AU. Central to this analysis is an equation for overall system a, which is derived from the power balance of a generalized "gain-limited" propulsion system. Results show that the gain required to achieve alpha approximately 10 (exp -1) kg/kW with foreseeable subsystem technology can vary from 50 to as high as 10,000, which is 2 to 5 orders of magnitude greater than current state-of-the art. However, order of magnitude improvements in propulsion subsystem mass and efficiency could reduce gain requirements to 10 to 1,000 - still a very challenging goal.

Chakrabarti, Suman↗
NASA NTRS2012

Accurate ab initio Quartic Force Fields of Cyclic and Bent HC2N Isomers

Highly correlated ab initio quartic force field (QFFs) are used to calculate the equilibrium structures and predict the spectroscopic parameters of three HC2N isomers. Specifically, the ground state quasilinear triplet and the lowest cyclic and bent singlet isomers are included in the present study. Extensive treatment of correlation effects were included using the singles and doubles coupled-cluster method that includes a perturbational estimate of the effects of connected triple excitations, denoted CCSD(T). Dunning s correlation-consistent basis sets cc-pVXZ, X=3,4,5, were used, and a three-point formula for extrapolation to the one-particle basis set limit was used. Core-correlation and scalar relativistic corrections were also included to yield highly accurate QFFs. The QFFs were used together with second-order perturbation theory (with proper treatment of Fermi resonances) and variational methods to solve the nuclear Schr dinger equation. The quasilinear nature of the triplet isomer is problematic, and it is concluded that a QFF is not adequate to describe properly all of the fundamental vibrational frequencies and spectroscopic constants (though some constants not dependent on the bending motion are well reproduced by perturbation theory). On the other hand, this procedure (a QFF together with either perturbation theory or variational methods) leads to highly accurate fundamental vibrational frequencies and spectroscopic constants for the cyclic and bent singlet isomers of HC2N. All three isomers possess significant dipole moments, 3.05D, 3.06D, and 1.71D, for the quasilinear triplet, the cyclic singlet, and the bent singlet isomers, respectively. It is concluded that the spectroscopic constants determined for the cyclic and bent singlet isomers are the most accurate available, and it is hoped that these will be useful in the interpretation of high-resolution astronomical observations or laboratory experiments.

Inostroza, Natalia↗
NASA NTRS1972

Design of non-interacting multivariable discrete time systems

The theory of decoupling a multivariable system with the help of state variable feedback is applied to discrete time systems. The system differential equations in the continuous time domain are converted to a discrete time representation. A discrete time controller is designed to control the overall input to the system such that a specified desired decoupled output response is obtained. The decoupled system behaves as a set of single-input, single-output systems and state variable techniques can be easily applied to control each output individually. Control is achieved by periodically sampling the inputs and all the states and feeding them back through a controller. For linear time invariant systems the control is time invariant. The basic theory of decoupling involves feeding back all the states twice, first to decouple the system and then to achieve a desired response. The states of the system are computed with the help of a state estimator which calculates all the present states of the system so that on-line control can be applied to real time systems. The theory is applied to a model of a nuclear rocket engine.

Agrawal, B. L.↗
NASA NTRS2021

Compass Final Report: Nuclear Electric Propulsion (NEP)-Chemical Vehicle 1.2

Many previous studies have examined sending crews to and from Mars. The most economical involved a ‘conjunction’ class whereby the crew spends around 500 days on Mars waiting for a ‘cheap’ return. The total mission time results in over a 1000-day mission duration (about 3 years). Given the current experience level of only one year on the International Space Station (ISS), it of interest to reduce that time to only two years, thus reducing risk and minimizing required Mars surface infrastructure. The Phase 1.1 Study goal was stated as follows, “Determine the feasibility of a two-year roundtrip class Mars mission concept of operation that enables boots on Mars no later than 2036.” While the Phase1 study did show feasibility for the NEP-Chemical option, the 2036 Opposition opportunity was found to stress the schedule due to proposed technology development schedules. A 2039 Opposition (which requires even more energy than the 2036 case) was chosen as representative for Phase 1.2. Phase 1.2 also sought to further refine the concept, building on the feasibility, but addressing several challenges brought by the red team and habitat team. Given the date of 2039, nearer term technologies, primarily nuclear thermal and nuclear electric were deemed as the most viable for these missions. As will be shown, the energy required to perform such a mission in only two years (for the 2039 opportunity at least) is about three times that of the three-year conjunction mission. The rocket equation shows that this mission would then require several times the propellant of the three-year mission unless the specific impulse (ISP) of the propulsion system can be increased. Based on lunar needs, a limit of five Space Launch System (SLS) launchers with 8.4m fairings was imposed for the piloted transportation portion of the mission, limiting the size of the system. When using nuclear electric propulsion, the main limiting factor was packaging the required radiator area. The higher Isp nuclear electric propulsion (NEP) system option is described herein but with a twist: in order to keep the size of radiators packageable in one SLS and use proven reactor power system technology (~1200K reactor outlet temperature and superalloy-class Brayton) the NEP system had to be combined with a chemical propulsion system. This combination of electric propulsion and high thrust chemical was found to be useful in previous design studies combining solar electric propulsion (SEP) and chemical propulsion. Such a combination allowed the low-thrust system to provide significant change in velocity (∆V) during the interplanetary portions of the mission, thereby notably reducing the ∆V required by the high thrust system to capture and depart from the Mars gravity well. Here the high thrust ‘impulsive’ system is more efficient due to the Oberth Effect. A plethora of trades, both at the mission and system level, as well as the subsystem level were performed to develop these vehicle concepts. An entire family of NEP-Chemical transportation vehicles is described herein. The main driver and the primary focus was the piloted vehicle but additional concepts for cargo were performed using the same ‘building blocks’ in order to reduce costs and provide commonality.

Nuclear Power↗
NASA NTRS1998

Nuclear modules for space electric propulsion

Analysis of interplanetary cargo and piloted missions requires calculations of the performances and masses of subsystems to be integrated in a final design. In a preliminary and scoping stage the designer needs to evaluate options iteratively by using fast computer simulations. The Oak Ridge National Laboratory (ORNL) has been involved in the development of models and calculational procedures for the analysis (neutronic and thermal hydraulic) of power sources for nuclear electric propulsion. The nuclear modules will be integrated into the whole simulation of the nuclear electric propulsion system. The vehicles use either a Brayton direct-conversion cycle, using the heated helium from a NERVA-type reactor, or a potassium Rankine cycle, with the working fluid heated on the secondary side of a heat exchanger and lithium on the primary side coming from a fast reactor. Given a set of input conditions, the codes calculate composition. dimensions, volumes, and masses of the core, reflector, control system, pressure vessel, neutron and gamma shields, as well as the thermal hydraulic conditions of the coolant, clad and fuel. Input conditions are power, core life, pressure and temperature of the coolant at the inlet of the core, either the temperature of the coolant at the outlet of the core or the coolant mass flow and the fluences and integrated doses at the cargo area. Using state-of-the-art neutron cross sections and transport codes, a database was created for the neutronic performance of both reactor designs. The free parameters of the models are the moderator/fuel mass ratio for the NERVA reactor and the enrichment and the pitch of the lattice for the fast reactor. Reactivity and energy balance equations are simultaneously solved to find the reactor design. Thermalhydraulic conditions are calculated by solving the one-dimensional versions of the equations of conservation of mass, energy, and momentum with compressible flow.

Difilippo, F. C.↗
NASA NTRS1989

Electrical performance characteristics of high power converters for space power applications

The first goal of this project was to investigate various converters that would be suitable for processing electric power derived from a nuclear reactor. The implementation is indicated of a 20 kHz system that includes a source converter, a ballast converter, and a fixed frequency converter for generating the 20 kHz output. This system can be converted to dc simply by removing the fixed frequency converter. This present study emphasized the design and testing of the source and ballast converters. A push-pull current-fed (PPCF) design was selected for the source converter, and a 2.7 kW version of this was implemented using three 900 watt modules in parallel. The characteristic equation for two converters in parallel was derived, but this analysis did not yield any experimental methods for measuring relative stability. The three source modules were first tested individually and then in parallel as a 2.7 kW system. All tests proved to be satisfactory; the system was stable; efficiency and regulation were acceptable; and the system was fault tolerant. The design of a ballast-load converter, which was operated as a shunt regulator, was investigated. The proposed power circuit is suitable for use with BJTs because proportional base drive is easily implemented. A control circuit which minimizes switching frequency ripple and automatically bypasses a faulty shunt section was developed. A nonlinear state-space-averaged model of the shunt regulator was developed and shown to produce an accurate incremental (small-signal) dynamic model, even though the usual state-space-averaging assumptions were not met. The nonlinear model was also shown to be useful for large-signal dynamic simulation using PSpice.

Stuart, Thomas A.↗
NASA NTRS2019

Constraining the Neutron Star Mass–Radius Relation and Dense Matter Equation of State with NICER. I. The Millisecond Pulsar X-Ray Data Set

We present the set of deep Neutron Star Interior Composition Explorer (NICER) X-ray timing observations of the nearby rotation-powered millisecond pulsars PSRs J0437−4715, J0030+0451, J1231−1411, and J2124−3358, selected as targets for constraining the mass–radius relation of neutron stars and the dense matter equation of state (EoS) via modeling of their pulsed thermal X-ray emission. We describe the instrument, observations, and data processing/reduction procedures, as well as the series of investigations conducted to ensure that the properties of the data sets are suitable for parameter estimation analyses to produce reliable constraints on the neutron star mass–radius relation and the dense matter EoS. We find that the long-term timing and flux behavior and the Fourier domain properties of the event data do not exhibit any anomalies that could adversely affect the intended measurements. From phase-selected spectroscopy, we find that emission from the individual pulse peaks is well described by a single-temperature hydrogen atmosphere spectrum, with the exception of PSR J0437−4715, for which multiple temperatures are required.

Neutron stars↗
NASA NTRS2007

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗