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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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Review of recent in-house Stirling controller work at the NASA Glenn Research Center with a focus on controllers and power transmission for a Stirling-based Fission Surface Power (FSP) system.
Polymer electrolyte (PE)-based solid-state batteries (PE-SSBs) made with high-voltage cathodes are known to suffer from severe capacity fade, stemming primarily from the poor oxidative stability of most PEs under high-voltage cycling conditions. PEs also suffer from greater ion-transport limitations compared to liquid or solid electrolytes. However, often, these limitations are collectively stated to be responsible for the observed capacity fade, and it is challenging to decouple the contributions of different factors. Herein, a tunable cell fabrication platform was developed to systematically investigate and decouple the two primary capacity fade drivers (cell impedance growth and kinetic limitations), while keeping the other cell parameters constant. Three PE types with distinct transport characteristics were compared. By utilizing a voltage profile analysis method, the contribution of the cell's internal impedance growth was quantitatively decoupled from the kinetic limitations stemming from the high concentration gradient in the polymer catholyte and slow charge transfer reactions. We demonstrate that the high interfacial impedance did not necessarily correlate with the high capacity fade rate. Kinetic limitations that are not reflected by impedance measurements can play a dominant role in causing cumulative capacity decay.
The proper curation of returned astromaterial samples is essential to ensure that high-quality scientific investigations can be conducted for decades, enabling future generations to address evolving research questions. The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center (hereafter JSC Curation) is responsible for curating all of NASA’s extraterrestrial samples. Under the governing document, NASA Procedural Requirement (NPR) 7100.5 “Curation of Extraterrestrial Materials”, JSC Curation is charged with “The curation of all extraterrestrial material under NASA control, including future NASA missions.” The Directive goes on to define Curation as including “...documentation, preservation, preparation, and distribution of samples for research, education, and public outreach.” JSC Curation has a long-standing legacy of curating extraterrestrial materials, including but not limited to Apollo and Luna lunar samples, Genesis solar wind samples, Stardust comet samples, asteroid samples (Hayabusa1, Hayabusa2, and OSIRIS-REx), and Antarctic Meteorite samples from a variety of parent bodies. Building on this foundation, the Artemis program introduces new challenges and opportunities for sample curation, requiring both the application of proven practices and the development of innovative solutions. The Artemis Collection will be curated using established protocols refined through decades of experience with Apollo and subsequent sample collections, including but not limited to the utilization of cleanrooms, custom nitrogen gloveboxes, specialized storage containers and tools; all of which have strict material utilization and prohibition requirements. These practices provide a robust framework for contamination control, documentation, and long-term preservation. However, Artemis samples may present unique scientific and operational requirements, including enhanced contamination control measures (relative to Apollo) driven by evolving science objectives. To meet these needs, JSC Curation is actively developing new technologies and protocols that extend beyond traditional approaches, ensuring that the integrity of samples is maintained under increasingly stringent standards. One critical area of innovation is the development of cold sample curation capabilities. Certain Artemis samples, particularly those from Permanently Shadowed Regions (PSRs) and cold environments, are expected to contain ices and volatile components that require preservation and handling at sub-zero or even cryogenic temperatures. JSC Curation is leveraging best practices from the cold and cryogenic sample industries, as well as other government agencies and academic experts, to design facilities and handling procedures that maintain sample integrity while enabling scientific access. The goal is to develop capabilities to allow researchers to investigate volatiles and other temperature-sensitive materials while minimizing chemical and physical alterations from their returned state. In summary, adaptive curation at JSC combines the reliability of proven methodologies with forward-looking innovations to meet the scientific and operational demands of Artemis. Through enhanced contamination control, advanced cold curation capabilities, and an understanding of known and evolving future science priorities, NASA is preparing to maximize the scientific return from Artemis samples and preserve their value for generations of researchers.
The objective of this research work has been to provide analytical background and support to the ongoing experimental program at NASA, White Sands Test Facility, involving testing composite overwrapped pressure vessels (COPV) for impact damage and cyclic pressurization. Preliminary theoretical basis, including the governing equations for a shallow shell subjected to internal pressure, has been established. Effects of the Griffith type cracks on the structural integrity of the cylindrical vessel were evaluated by methods of Fracture Mechanics. The results indicate that the effective mass of the pressure vessel is an important factor influencing the response to impact events. We also have found that the material properties of the target, contained in the constitutive equations of the composite attached to the Aluminum liner, dominate the impact event in the low velocity range, the material properties become less important, while the target mass distribution and the impactor mass become more significant as the velocity of the impactor increases. Therefore, at high-velocity impact it is not only the kinetic energy of the impactor but also its mass which has a significant effect on the dynamics of the event, and consequently on the induced damage. This work also suggests a methodology for an assessment of the rate of loading effects on the degradation of the material toughness associated with a high-velocity impact where the rate effects become significant. To model the rate dependence of the material response a viscoelastic-plastic constitutive equations were assumed, and on this basis predictions are made regarding the rate dependent material resistance curve. Other dynamic phenomena associated with the impact event have been treated in the framework of the Computational Mechanics using the courtesy of Prof. P. Guebelle and his graduate student at University of Illinois at Urbana-Champaign who have an access to a super-fast computer located on their campus. Finally, the guidelines for a follow-up research program are provided in the body of this report. They address three major areas: theoretical research, numerical studies, and further experimental work.
Antiferromagnetic Weyl semimetals based on Mn 3 X(X = Ge, Sn, Ga) kagome compounds exhibit the same ferromagnetic-like responses, including anomalous Hall, Nernst, and magneto-optical effects, as recently discussed for altermagnets. Driven by the Berry curvature due to Weyl fermions, these materials show a disproportionately large magnitude of electromagnetic effects even in the absence of large magnetization. For applications it is crucial to realize these responses in a wide range of temperatures both below and above 300 K. While stoichiometric Mn 3 X materials do not offer optimal performance, we show that Mn 3 Sn 1−x Ga x sputtered films with a variable composition offers a tunable Néel temperature, T N ≈ 425 ± 6–500 ± 15 K, which is crucial for device applications, together with a large tunable anomalous Hall effect. Our thin film growth method enables continuous and precise control over the film composition between x = 0 and x = 1. Through a detailed magnetization and Hall transport, we establish the magnetic phase diagram for the hexagonal Mn 3 Sn 1−x Ga x . Our results reveal an enhanced T N and antichiral magnetic phase in Ga-doped Mn 3 Sn and an enhanced anomalous Hall magnitude in Sn-doped Mn 3 Ga compared to their stoichiometric undoped forms. Our work demonstrates a route to optimize the technologically relevant antiferromagnets for various applications.
The International Space Station (ISS) primary Electric Power System (EPS) was originally designed to use Nickel-Hydrogen (Ni-H2) batteries to store electrical energy. The electricity for the ISS is generated by its solar arrays, which charge batteries during insolation for subsequent discharge during eclipse. The Ni-H2 batteries were designed to operate at a 35 depth of discharge (DOD) maximum during normal operation in a Low Earth Orbit. In 2010, the ISS Program began the development of Lithium-Ion (Li-Ion) batteries to replace Ni-H2 batteries approaching the end of their useful life and concurrently funded a Li-Ion ORU (Orbital Replacement Unit) and cell life testing project. The first set of 6 Li-ion battery replacements was launched in December 2016 and deployed in January 2017. This paper will discuss the Li-ion battery on-orbit cycling and the status of the Li-Ion cell and ORU life cycle testing.
An efficient battery manufacturing process is the key to the mass production of Electric Vehicles (EV), in which drying is one of the most energy-intensive steps significantly influencing the battery cell performance. An accurate 3D CFD model for drying is essential for predicting the drying mechanism and optimizing its parameters. By optimizing the drying process, it is possible to reduce energy consumption and cost during battery manufacturing, minimize binder loading and maximize active material loading to achieve superior electrochemical performances and facilitate wider and faster public adoption of EV. This project aims to optimize the drying process during electrode manufacturing by leveraging high-fidelity, porous electrode simulations for solvent evaporation. By optimizing this process, we seek to reduce energy consumption during battery manufacturing, while minimizing binder loading and maximizing active material loading, with the overall goal of enhancing electrical vehicle performance.
Team functioning is integral to success in future long term space exploration missions. Proactively detecting declines in team functioning can mitigate conflict and ensure mission success. This project developed a speech-based artificial intelligence (AI) system that unobtrusively predicts degradation in team functioning, including performance and cohesion, in the Human Exploration Research Analog (HERA) Campaigns 4 and 5. The AI system conducted automated analysis of the prosodic (tone of voice) and linguistic (language content) components of speech, modeling interpersonal dynamics at both the turn-taking and day-wide levels. We investigated team functioning via observing structured interactions (i.e., multi-mission space exploration vehicle-extra vehicular activity [MMSEV-EVA], team interaction battery [TIB]) and unstructured interactions before the MMSEV-EVA task. We developed machine learning models to predict team functioning (objective task accuracy, self reported team efficacy and self reported team cohesion) by analyzing OpenSmile acoustic features, linguistic descriptors extracted via the linguistic inquiry and word count (LIWC) dictionary, and semantic embeddings. In the TIB, static models using logistic regression and random forests were not able to predict task accuracy, but predicted team efficacy and cohesion during both the decision making and relational tasks to a moderate level (60-70%). Majority voting on the individual turns to predict day long team efficacy further increased accuracies (70-80%). Finally, long short-term memory (LSTM) models showed the best performance across all variables (80-91%), including task performance. In the MMSEV-EVA, static models achieved an accuracy of 60% with majority voting, which increased to 80% through the incorporation of mission day as a variable, accounting for the learning effect. A key finding across both tasks was the "team-dependent" nature of these interactions; models achieved much higher accuracy when trained on prior days of the same team's data rather than attempting to generalize across entirely different teams, with even 1-2 days of prior data per team achieving 5-15% improvement over team-independent models. In addition, the incorporation of pre-task data from the same team also improves model performance, e.g., incorporating data from the decision-making task of the TIB, which preceded the relational task, improved the prediction of team efficacy and cohesion during the latter. We compared model performance when trained on machine-generated data compared to data that had been further corrected by human annotators. Overall, models trained on human-corrected data exhibited a modest improvement in performance, particularly when acoustic features were used. We found no significant correlation between word error rate (WER) and model accuracy (r(55) = -0.08, p = 0.51), but model’s accuracy was significantly higher for medium/high quality transcription (0.74 (SD = 0.48)) compared to the low-quality group (0.64 (SD = 0.36)) (t(63)=2.82, p = 0.006). Based on these, several design recommendation emerge, that could inform Standards at NASA. Models predicting team functioning should incorporate at least one to two days of historical interaction data, include brief pre-task discussions, and explicitly model temporal learning effects, especially for longer operational tasks. Minimum quality standards for automated speech-processing pipelines are needed, given the performance gains observed with manually corrected acoustic data. Finally, systems should leverage both acoustic features and language embeddings in complementary ways, with modality choices and fusion strategies tailored to mission context, task demands, and data quality requirements.
Advanced electrified aircraft propulsion (EAP) concepts with integrated power, propulsion, and thermal systems require the development of equally sophisticated controllers to fly safe and efficient missions. Hybrid electric aircraft utilize electric machines mechanically coupled to the engine shafts to extract and insert power for a variety of purposes. Additionally, electric machines may drive propulsive fans pulling from a combination of on-board energy storage devices and engine extracted power. NASA’s investment in hybrid electric aircraft hardware-in-the-loop testing enables controls research on representative engine models using a novel emulation and scaling methodology. High-voltage, high-power electrical powertrain presents several technical risks at altitude. High-power requires high efficiency to minimize losses. Superconducting electric machines and power distribution research at NASA has identified key challenges with potential controls solutions. These risks necessitate the development of controllers robust to model uncertainty, disturbances, and fault conditions. System health management and fault detection schemes play an important role in a multi-layer controls approach that utilizes a supervisor which oversees inner loops for the highly coupled power, propulsion, and thermal systems. Such a supervisory controller enables coordinates energy transfer between engines, energy storage devices, electric machines, propulsors, and heat exchangers. Existing methods have shown an improvement in engine operability using the hybrid electric powertrain.
The Habitable Worlds Observatory (HWO) is NASA’s next large space telescope, selected by the 2020 Decadal Survey in Astronomy and Astrophysics to search for and characterize habitable exoplanets while enabling a broad range of transformative astrophysics. In August 2024, the HWO Technology Maturation Project Office (TMPO) was formed to begin exploring the HWO science, technology, and mission architectures toward a Mission Concept Review (MCR) at the end of the decade. A primary deliverable of this effort is this technology development plan that identifies critical technologies that enable the mission, defines a process for assessing the readiness of those technologies, and outlines a strategy for developing those technologies to a Technology Readiness Level (TRL) of 5 before the MCR. This document covers technologies organized along three “tracks”: Coronagraph System technologies, Ultra-stable Telescope System technologies, and High-sensitivity Ultraviolet and Visible Instrumentation technologies. Additional emerging and enhancing technologies are also discussed.
To meet California and the nation's ambitious energy targets, energy use in the building sector must drop dramatically. Windows continue to be the lowest thermally performing envelope system in the nation's buildings, resulting in poor overall envelope performance and potential impacts to human health and comfort. Current best practice new window performance is typically met by double-pane low-solar-gain glazing. Thin-glass triple-pane windows are a highly promising next step forward in performance and have been deployed in two California multi-family sites to quantify field performance and building energy savings. The technology assessed offers the performance benefits of traditional triple-pane but with little increase in weight or cost, enabling incremental costs competitive with alternative energy reduction solutions for the building envelope. This paper covers a detailed investigation into the demonstration project and measured performance benefits of the windows after a full year of data collection.
Integrating lignin into a cellulosic ethanol plant for the co-production of lignin-based jet fuel (LJF) in aqueous phase offers a significant opportunity to boost operational efficiency, economic viability, carbon conversion, and the overall sustainability of biofuel and chemical production. LJF is lignin-structure-based jet fuel blendstocks primarily composed of alkyl-substituted mono-, bi-, and tri-cyclohexanes. It exhibits high energy density, potential for low emissions, and favourable blend characteristics that comply with drop-in specifications. An overview of lignin feedstock, catalytic processes, LJF chemical compositions, fuel properties tests, and techno-economic analysis (TEA) and life cycle assessment (LCA) indicate that (1) the reactivity of lignin plays a crucial role in its structure transformation to LJF molecules; (2) catalytic processing of lignin to LJF can occur through a simultaneous depolymerization and hydrodeoxygenation process, bypassing the intermediate step of producing and upgrading lignin-derived oil; (3) LJF's uniqueness molecules making it more promising for high energy content and low emission jet fuel properties for next generation sustainable aviation fuel (SAF); and (4) TEA and LCA demonstrate that LJF is not only potentially cost-effective but also offers favourable carbon footprint compared to other SAFs. In conclusion, this review highlights the most recent advancements in LJF technology, along with the challenges and opportunities that lie ahead in fulfilling its potential.
Over the last decades flight vehicles such as aircraft and helicopters entering service and requiring increased operational effectiveness have with few exceptions experienced prolonged flight test development to achieve full certification. In many cases the original requirements had later to be reduced to enable release to service. The impact on the customer, and manufacturer has been considerable leading to increased costs and or reduced operational capabilities. These costly experiences are largely a result of the flight vehicle not behaving as modelled and designed. The evaluation of flight test data can be used as a tool for validating windtunnel results and mathematical models describing the flight dynamical behaviour. In this sense the uncertainty of important aerodynamic stability and control parameters can be reduced and the confidence of aircraft mathematical models improved. An additional important factor comes from the implementation of active control systems offering the promise of significantly increased flight vehicle performance and operational capability. This approach extends the traditional trade-offs between aerodynamics, structures and propulsion systems to include full- time, full-authority fly-by-wire/light systems. It is imperative that the aerodynamic stability and control parameters of such integrated flight and propulsion control systems have to turn out inflight as predicted, since inherent stability margins will be lower and the flight control system must correct these deficiencies to provide flight critical redundancy and safety. With the methodology of system identification from flight tests it is possible to sense the control inputs and the flight vehicle reactions Such as accelerations, rates and attitudes. The mathematical model, e.g. the model structure and parameters, has to be determined from the relationship of the measured control inputs and the system's responses. The aim of this symposium was to review the present state of the art of flight vehicle system and parameter identification techniques, and to provide a critical appraisal of current methods developed and applied to flight test data in a number of NATO nations. Particular emphasis was placed on practical aspects and lessons learned in order to generate information useful to the flight test community in industry and government agencies. The technical papers share invaluable experience and emphasize the advances of flight vehicle system identification over the last years to the point where confidence and robustness level is now reasonably high. The symposium covered overviews of identification methodologies, flight test techniques, recent aircraft and helicopter application programs, and a session of short papers covering up-to-the-minute flight test results. A final discussion included prepared comments from experts and concluded with key issues learned in the application of system identification and future research needs. The essential benefits to NATO nations can be condensed as follows: More accurate mathematical models for high bandwidth flight control systems, Improved assessment and evaluation of flying qualities, High fidelity mathematical models for flight vehicle development and mission training simulators, and generally, Reduced flight test time and costs.
This report details an effort to develop a retrofittable fuel/air injector for the FT4000® aeroderivative gas turbine that enables use of hydrogen as a carbon-free fuel for efficient power generation. The FT4000 engine’s low-NOx combustor was developed by Pratt & Whitney and RTX Technology Research Center with core technology from the Pratt & Whitney PW4000 turbofan aircraft engine. The current FT4000 production engine operates on either natural gas or No. 2 fuel oil with water injection to achieve high thermal efficiency and low emissions. This engine is fielded by Mitsubishi Power Aero and delivers 70 MW of power with a simple-cycle efficiency of over 41% when operating with wet compression. The work reported here advances the technology readiness level of the FT4000 combustor for operation with hydrogen, starting with an experimental assessment of the current production hardware with increasing hydrogen content mixed with natural gas and ending with improved nozzle concepts for fully robust operation with 100% hydrogen. High-pressure single-sector combustor rig tests have been completed, demonstrating the ability for the dual fuel nozzle to operate an FT4000 combustor on 100% hydrogen with low nitrogen oxide (NOx) emissions. Metal temperature measurements and video images of the flame structure from zero to 100% hydrogen highlight opportunities to improve the fuel nozzle robustness for high hydrogen conditions. The design of new fuel/air mixer concepts to improve durability and operability with high hydrogen levels was also completed. A total of eleven new concepts were developed and analyzed, ranging from modifications to the bill-of-materials nozzle to fully clean sheet designs. The concepts were evaluated with non-reacting and reacting flow evaluations to assess the performance of the new hardware designs. Non-reacting tests included Phase Doppler Particle Analysis (PDPA) for droplet size and velocity, mechanical patternation for liquid water flux, and planar laser induced fluorescence (PLIF) with acetone-seeding for gaseous fuel/air mixing characterization. Five scaled candidate fuel nozzle designs, in addition to a scaled bill-of-materials nozzle, were then successfully evaluated in an atmospheric pressure burner rig. The nozzles were evaluated for performance with natural gas, hydrogen/natural gas blends, and pure hydrogen. For 100% hydrogen, the nozzles were evaluated with and without water injection. Optical and infrared imaging of the flame and fuel nozzle was captured. NOx emissions were sampled from fixed emissions probes. The results show measurable differences between the various designs, and the data was used to down-select the two most promising designs to advance to future full pressure rig testing. Results from this study have cleared the current production FT4000 engines with dual fuel nozzles to operate at baseload power on blends of hydrogen mixed with natural gas and water. Two promising nozzle designs have been developed to enable fully robust operation with up to 100% hydrogen. These nozzles require validation at full baseload operating conditions before they can be introduced to the field.
Gamma-ray and X-ray spectrometers carried in the Service Modules of the Apollo 15 and Apollo 16 spacecraft were employed for compositional mapping of the lunar surface. The measurements involved the observation of the intensity and characteristic energy distribution of gamma rays and X-rays emitted from the lunar surface. A large-scale compositional map of over 10 percent of the lunar surface was obtained from an analysis of the observed spectra. The Apollo 15 flight was at a lunar orbital inclination of 29 degrees as compared with a 9-degree inclination of the Apollo 16 flight; thus, the projected ground track of the Apollo 15 flight covered a larger projected surface area than that of the Apollo 16 flight. The objective of the X-ray experiment was to measure the K spectral lines from Mg, Al, and Si. Spectra were obtained and the data were reduced to Al/Si and Mg/Si intensity ratios and ultimately to chemical ratios. Analyses of the results have indicated (1) that the Al/Si ratios are highest in the lunar highlands and considerably lower in the maria, and (2) that the Mg/Si concentrations generally show the opposite relationship. There is a tendency for the Al/Si values to increase from the western mare areas to the eastern limb highlands. There are distinct chemical contrasts between such features: as the small mare basins and the highland rims. The objective of the gamma-ray experiment was to measure the natural and cosmic-ray-induced activity emission spectrum. At this time, the elemental abundances for Th, U, K, Fe, Ti, Si, and O have been determined over a number of major lunar regions. Regions of relatively high natural radioactivity were found in the Mare Imbrium and Oceanus Procellarum regions. High spots of natural radioactivity were also found south of Fra Mauro; somewhat southwest of Archimedes, and south of Aristarchus. An enhanced region of natural radioactivity was found around Van de Graaff on the far side of tile Moon. In regions other than Mare Imbrium and Oceanus Procellarum, an anticorrelation between natural radioactivity and lunar elevation, as determined from the Apollo laser, altimeter, has been found. From the combined results of the gamma-ray and X-ray spectrometer experiments almost complete information concerning the major element composition of over 10 percent of the lunar surface has been obtained. Distributions have also been mapped for K, Th, and Ti. Interesting correlations between lunar topography and magnetic and gravitational properties have been found.
The search for new quantum spin liquid materials relies on systems with strong frustration such as spins on an ideal kagome lattice. However, lattice imperfections can have substantial effects which are as yet not well understood. In recent work, the two-dimensional kagome system YCu 3 (OH) 6 [(Cl 𝑥 Br (1−𝑥) ) 3−𝑦 (OH) 𝑦 ] has emerged as a leading candidate hosting a Dirac spin liquid which appears to survive at least for 𝑥 < 0.4, associated with alternating-bond-hexagon (ABH) disorder. Here in magnetic samples with 𝑥 = 0.58, 𝑦 = 0.1 we report unusual in-plane ferromagnetic canting (FM) of the in-plane antiferromagnet (AFM), with an unusually wide regime of short-ranged order, and propose theoretical models to explain this behavior. First, we show that Kitaev-type exchanges naturally arise on the kagome lattice to second order in the known Dzyaloshinskii-Moriya exchanges, and that these interactions can produce the unusual in-plane FM canting from antichiral AFM. Second, we propose a phenomenological model of weakly FM-canted spin clusters to describe the short-ranged regime and analyze quantum fluctuations in an ABH toy model to show how ABH disorder can stabilize this regime. Here, the combination of experimental observation and theory suggests that kagome-Kitaev interactions and ABH disorder are necessary for describing the magnetic fluctuations in this family of materials, with potential implications for the proposed proximate spin liquid phase.
Genomic data from contemporary and historical samples often need to be coupled for evolutionary reconstructions of multitaxon complexes. However, the genetic data recovered from historical samples may result only in ultra-low coverage whole-genome sequences (ulcWGS; <0.15× depth), leading to inaccurate evolutionary inferences given a preponderance of missing data. Using the Galapagos giant tortoise radiation as a study system (Chelonoidis spp., composed of 13 extant and four extinct lineages), we assembled a novel methodological pipeline that removes potential noise introduced by the missing data and enhances the evolutionary signal from ulcWGS samples. We leveraged existing tools for phylogenomic placement (EPA-ng), population genomic structure (smartsnp) and admixture (Admixfrog, NGSadmix) to demonstrate that the evolutionary history of samples can be uncovered with sequencing depths as low as 0.008–0.139×. Importantly, these approaches do not use genotype imputation of the ulcWGS samples, which would require extensive reference datasets. Our application to two cases of extinct lineages of Galapagos giant tortoises, with and without references from the same lineage, demonstrates the general value of the approach. We confirm where the extinct lineages from San Cristóbal and Santa Fe islands fit into the Galapagos giant tortoise radiation, and that these lineages were evolutionarily distinct entities.
A typical Bayesian inference on the values of some parameters of interest q from some data D involves running a Markov Chain (MC) to sample from the posterior $p$($q$,$n$|$D$) $\propto$ $\mathcal{L}$($D$|$q$,$n$)$p$(q)$p$($n$), where n are some nuisance parameters with a separable prior. In some cases, the nuisance parameters are high-dimensional, and their prior p(n) is itself defined only by a set of samples that have been drawn from some other MC. The MC for the posterior will typically require evaluation of p(n) at arbitrary values of n, i.e., one needs to provide a density estimator over the full n space from the provided samples. But the high dimensionality of n hinders both the density estimation and the efficiency of the MC for the posterior. We describe a solution to this problem: a linear compression of the n space into a much lower-dimensional space u, which projects away directions in n space that cannot appreciably alter $\mathcal{L}$. The algorithm for doing so is a slight modification to principal components analysis, and is less restrictive on p(n) than other proposed solutions to this issue. We demonstrate this “mode projection” technique using the analysis of 2-point correlation functions of weak lensing fields and galaxy density in the Dark Energy Survey, where n is a binned representation of the redshift distribution n(z) of the galaxies.