Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “skew mitigation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

8 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Synthetic Jet Interaction With A Turbulent Boundary Layer Flow

Perhaps one of the more notable advances to have occurred in flow control technology in the last fifteen years is the application of surface-issuing jets for separation control on aerodynamic surfaces. The concept was introduced by Johnston and Night (1990) who proposed using circular jets, skewed and inclined to the wall, to generate streamwise vortices for the purpose of mitigating boundary layer separation. The skew and inclination angles have subsequently been shown to affect the strength and sign of the ensuing vortices. With a non-circular orifice, in addition to skew and inclination, the yaw angle of the major axis of the orifice can influence the flow control effectiveness of the jet. In particular, a study by Chang arid Collins (1997) revealed that a non-circular orifice, yawed relative to the freestream, can be used to control the size and strength of the vortices produced by the control jet. This early work used jets with only a steady injection of mass. Seifert et al. revealed that an unsteady blowing jet, could be as effective at separation control as a steady jet but with less mass flow. Seifert et al. showed that small amplitude blowing oscillations superimposed on a low momentum steady jet Was the most effective approach to delaying separation on a NACA 0015 airfoil at post-stall angles of attack. More recent work suggests that perhaps the most efficient jet control effect comes from a synthetic (oscillatory) jet where the time-averaged mass flux through the orifice is zero, but the net wall normal momentum is non-zero. The control effectiveness of synthetic jets has been demonstrated for several internal and external flow fields used synthetic jet control on a thick, blunt-nosed airfoil to delay stall well beyond the stall angles for the uncontrolled airfoil and with a dramatic increase in the lift-to-drag performance. Amitay et al. used an array of synthetic jets to mitigate flow separation in curved and diffusing ducts. While the control effectiveness of synthetic jet actuators in an application setting has been confirmed through a number of studies, the fluid dynamic mechanism by which control is effected is not well understood. Issues like yaw angle arid velocity ratio that have been studied for steady control jets have not been investigated for synthetic jets. Moreover, the role played by the inherently unsteady nature of a synthetic jet in the interaction with the controlled flow is not known. Some recent work by Rinehart and Glazer and Smith suggests that away from tile immediate vicinity of the jet orifice the flow field is steady in the mean, and that the interaction of a synthetic jet and a boundary layer creates a secondary flow in the boundary layer consisting primarily of streamwise vortices.

Smith, Douglas R.↗
NASA NTRS2022

Detection and Characterization of Instrumental Transients in LISA Pathfinder and Their Projection to LISA

The LISA Pathfinder (LPF) mission succeeded outstandingly in demonstrating key technologicalaspects of future space-borne gravitational-wave detectors, such as the Laser Interferometer SpaceAntenna (LISA). Specifically, LPF demonstrated with unprecedented sensitivity the measurementof the relative acceleration of two free-falling cubic test masses. Although most disruptive non-gravitational forces have been identified and their effects mitigated through a series of calibrationprocesses, some faint transient signals of yet unexplained origin remain in the measurements. If theyappear in the LISA data, these perturbations (also called glitches) could skew the characterizationof gravitational-wave sources or even be confused with gravitational-wave bursts. For the firsttime, we provide a comprehensive census of LPF transient events. Our analysis is based on aphenomenological shapelet model allowing us to derive simple statistics about the physical featuresof the glitch population. We then implement a generator of synthetic glitches designed to be usedfor subsequent LISA studies, and perform a preliminary evaluation of the effect of the glitches onfuture LISA data analyses.

Quentin Baghi↗
NASA NTRS2001

Fundamentals of Digital Engineering: Designing for Reliability

The concept of designing for reliability will be introduced along with a brief overview of reliability, redundancy and traditional methods of fault tolerance is presented, as applied to current logic devices. The fundamentals of advanced circuit design and analysis techniques will be the primary focus. The introduction will cover the definitions of key device parameters and how analysis is used to prove circuit correctness. Basic design techniques such as synchronous vs asynchronous design, metastable state resolution time/arbiter design, and finite state machine structure/implementation will be reviewed. Advanced topics will be explored such as skew-tolerant circuit design, the use of triple-modular redundancy and circuit hazards, device transients and preventative circuit design, lock-up states in finite state machines generated by logic synthesizers, device transient characteristics, radiation mitigation techniques. worst-case analysis, the use of timing analyzer and simulators, and others. Case studies and lessons learned from spaceflight designs will be given as examples

Katz, R.↗
NASA NTRSDate not supplied

Understanding the Impact of Unobservable Variables on the Performance of Predictive Models: The Need for Feature Space Partitioning and Fusion

When developing predictive models over a dataset, the model is globally optimized across the entire feature space to learn a decision boundary. However, when unobservable variables—which cannot be measured or estimated—interact with the observable variables, this can negatively impact the optimization applied to the decision boundary since the data samples introduced by unobservable variables may have little to no association with the applied global optimization. This, consequently, penalizes the entire decision boundary and model performance. This paper examines some of the detrimental effects of unobservable variables, particularly their role in creating new modes in the distribution of observable variables and reducing the separability of class distributions. Such challenges result in skewed or warped decision boundaries and decreased accuracy of model predictions, particularly for interpretable models like logistic regression and decision trees. Through two illustrative case examples, we highlight the need to address the challenges imposed by unobservable variables. We propose a strategy to mitigate these challenges by creating local regions within the feature space through partitioning. This enables the optimization of local models within the regions to overcome the impact of unobservability in different feature space localities. Research into a more sophisticated partitioning strategy and where the partition should be relative to the sample of interest is left as future work. Through the analysis of the impact of unobservability and the development of a partitioning method, we demonstrate the clear need for a partitioning strategy that integrates knowledge from multiple local models to estimate risk factors using information fusion. Thus, we establish the foundation and motivation for using partitioning and information fusion to overcome the effects of unobservability in predictive models. Formal fusion methods, such as Dempster-Shafer theory, can better leverage the information from local regions to improve the performance of interpretable predictive models in the presence of unobservable variables.

Time Series Data↗
NASA NTRS2023

DES Y3 + KiDS-1000: Consistent Cosmology Combining Cosmic Shear Surveys

We present a joint cosmic shear analysis of the Dark Energy Survey (DES Y3) and the Kilo-Degree Survey (KiDS-1000) in a collaborative effort between the two survey teams. We find consistent cosmological parameter constraints between DES Y3 and KiDS-1000 which, when combined in a joint-survey analysis, constrain the parameter S 8 =σ 8 √(Ω m /0.3) with a mean value of 0.790 +0.018 −0.014. The mean marginal is lower than the maximum a posteriori estimate, S 8 =0.801, owing to skewness in the marginal distribution and projection effects in the multi-dimensional parameter space. Our results are consistent with S 8 constraints from observations of the cosmic microwave background by Planck, with agreement at the 1.7 σ level. We use a Hybrid analysis pipeline, defined from a mock survey study quantifying the impact of the different analysis choices originally adopted by each survey team. We review intrinsic alignment models, baryon feedback mitigation strategies, priors, samplers and models of the non-linear matter power spectrum.

cosmology↗
NASA NTRS2018

Climate Shifts Within Major Agricultural Seasons for +1.5 and +2.0 °C Worlds: HAPPI Projections and AgMIP Modeling Scenarios

This study compares climate changes in major agricultural regions and current agricultural seasons associated with global warming of +1.5 or +2.0 °C above pre-industrial conditions. It describes the generation of climate scenarios for agricultural modeling applications conducted as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Global and Regional Assessments. Climate scenarios from the Half a degree Additional warming, Projections, Prognosis and Impacts project (HAPPI) are largely consistent with transient scenarios extracted from RCP4.5 simulations of the Coupled Model Intercomparison Project phase 5 (CMIP5). Focusing on food and agricultural systems and top-producing breadbaskets in particular, we distinguish maize, rice, wheat, and soy season changes from global annual mean climate changes. Many agricultural regions warm at a rate that is faster than the global mean surface temperature (including oceans) but slower than the mean land surface temperature, leading to regional warming that exceeds 0.5 °C between the +1.5 and +2.0 °C Worlds. Agricultural growing seasons warm at a pace slightly behind the annual temperature trends in most regions, while precipitation increases slightly ahead of the annual rate. Rice cultivation regions show reduced warming as they are concentrated where monsoon rainfall is projected to intensify, although projections are influenced by Asian aerosol loading in climate mitigation scenarios. Compared to CMIP5, HAPPI slightly underestimates the CO2 concentration that corresponds to the +1.5 °C World but overestimates the CO2 concentration for the +2.0 °C World, which means that HAPPI scenarios may also lead to an overestimate in the beneficial effects of CO2 on crops in the +2.0 °C World. HAPPI enables detailed analysis of the shifting distribution of extreme growing season temperatures and precipitation, highlighting widespread increases in extreme heat seasons and heightened skewness toward hot seasons in the tropics. Shifts in the probability of extreme drought seasons generally tracked median precipitation changes; however, some regions skewed toward drought conditions even where median precipitation changes were small. Together, these findings highlight unique seasonal and agricultural region changes in the +1.5 °C and +2.0 °C worlds for adaptation planning in these climate stabilization targets.

Alexander C. Ruane↗
NASA NTRS2021

Half of global methane emissions come from highly variable aquatic ecosystem sources

Atmospheric methane is a potent greenhouse gas that plays a major role in controlling the Earth’s climate. The causes of the renewed increase of methane concentration since 2007 are uncertain given the multiple sources and complex biogeochemistry. Here, we present a metadata analysis of methane fluxes from all major natural, impacted and human-made aquatic ecosystems. Our revised bottom-up global aquatic methane emissions combine diffusive, ebullitive and/or plant-mediated fluxes from 15 aquatic ecosystems. We emphasize the high variability of methane fluxes within and between aquatic ecosystems and a positively skewed distribution of empirical data, making global estimates sensitive to statistical assumptions and sampling design. We find aquatic ecosystems contribute (median) 41% or (mean) 53% of total global methane emissions from anthropogenic and natural sources. We show that methane emissions increase from natural to impacted aquatic ecosystems and from coastal to freshwater ecosystems. We argue that aquatic emissions will probably increase due to urbanization, eutrophication and positive climate feedbacks and suggest changes in land-use management as potential mitigation strategies to reduce aquatic methane emissions.

aquatic ecosystem↗
NASA NTRSDate not supplied

Bone Health: An Integrated Approach to Monitoring the Dynamic Net Bone Mineral Balance During 2-, 6- and 12-Month Missions Aboard the ISS

Spaceflight-induced bone loss is a significant health concern for astronauts which is only partially mitigated by established countermeasures such as resistive exercise, vitamin D supplementation, and nutritional support. These countermeasures have proven adequate for nominal 6-month missions aboard the ISS, but individual crewmembers may experience a degree of net bone loss which varies significantly. Estimates of whole-body bone mineral content (BMC) made using DXA show the mean change in BMC averages only -1 % during a nominal 6-month ISS mission. However, the observed range of interpersonal variation extends from + 1 % to -5 % per mission for crewmembers using ARED as a primary bone loss countermeasure [1]. This highlights two significant outstanding issues: (1) we currently cannot predict which crewmembers will experience greater or lesser extents of net bone loss during space flight; and (2) because of limited information regarding the dynamics of net bone loss during space flight, we cannot currently extrapolate the net bone loss rates observed during 6-month ISS missions to even longer duration missions envisioned for the Moon and Mars. The overall goal of the Bone Health project is to improve our understanding of how net bone mineral balance dynamically evolves during 2-12 months of spaceflight using integrated biochemical and calcium isotopic measurements. This will provide a foundation for estimating the possible range of changes in BMC that might be expected during even longer duration missions. As part of the Integrated 1-Year Mission Project, we aim to address these issues by (1) determining the time course of net whole-body bone mineral balance during 2-month, 6-month, and 12-month missions aboard the ISS, (2) examining the interpersonal variation in net bone loss/gain to determine whether this distribution is skewed with rare individuals experiencing above average rates of net bone loss, and (3) exploring possible predictors for individuals who will experience above or below average rates of net bone loss.

G W Gordon↗