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Reliability Sensitivity Analysis and Design Optimization of Composite Structures Based on Response Surface Methodology

This report discusses the development and application of two alternative strategies in the form of global and sequential local response surface (RS) techniques for the solution of reliability-based optimization (RBO) problems. The problem of a thin-walled composite circular cylinder under axial buckling instability is used as a demonstrative example. In this case, the global technique uses a single second-order RS model to estimate the axial buckling load over the entire feasible design space (FDS) whereas the local technique uses multiple first-order RS models with each applied to a small subregion of FDS. Alternative methods for the calculation of unknown coefficients in each RS model are explored prior to the solution of the optimization problem. The example RBO problem is formulated as a function of 23 uncorrelated random variables that include material properties, thickness and orientation angle of each ply, cylinder diameter and length, as well as the applied load. The mean values of the 8 ply thicknesses are treated as independent design variables. While the coefficients of variation of all random variables are held fixed, the standard deviations of ply thicknesses can vary during the optimization process as a result of changes in the design variables. The structural reliability analysis is based on the first-order reliability method with reliability index treated as the design constraint. In addition to the probabilistic sensitivity analysis of reliability index, the results of the RBO problem are presented for different combinations of cylinder length and diameter and laminate ply patterns. The two strategies are found to produce similar results in terms of accuracy with the sequential local RS technique having a considerably better computational efficiency.

Rais-Rohani, Masoud↗

Interannual and Long-Term Changes in Middle Atmosphere Temperature from Haloe

Radiative models of the middle atmosphere indicate that the largest temperature response due to steadily increasing amounts of atmospheric CO2 should occur at pressure altitudes between 1 and 0.1 hPa (about 48 to 64 km) and be of the order of 0.5 to 0.6 K/decade on a pressure surface . Such a rate assumes that there is no trend in ozone or in the dissipation of wave activity for that region of the middle atmosphere. This rate of cooling is only of the order of 0.20 to 0.25% per decade, which is a small trend to discern from observations. We have analyzed the 11-year, Version 19 (or V19) temperature versus pressure profile (or T(p)) time series from the UARS Halogen Occultation Experiment (HALOE) for such trends at selected pressure levels. The HALOE T(p) time series are being obtained using CO2 transmission data centered at 2.8 micrometers and from a single instrument that uses the limb solar occultation measurement geometry, which provides significant advantages for the calibration of its single profiles.

Remsbwerg, Ellis↗

Finite Element Simulations of Two Vertical Drop Tests of F-28 Fuselage Sections

In March 2017, a vertical drop test of a forward fuselage section of a Fokker F-28 MK4000 aircraft was conducted as part of a joint NASA/FAA project to investigate the performance of transport aircraft under realistic crash conditions. In June 2017, a vertical drop test was conducted of a wing-box fuselage section of the same aircraft. Both sections were configured with two rows of aircraft seats, in a triple-double configuration. A total of ten Anthropomorphic Test Devices (ATDs) were secured in seats using standard lap belt restraints. The forward fuselage section was also configured with luggage in the cargo hold. Both sections were outfitted with two hat racks, each with added ballast mass. The drop tests were performed at the Landing and Impact Research facility located at NASA Langley Research Center in Hampton, Virginia. The measured impact velocity for the forward fuselage section was 346.8-in/s onto soil. The wing-box section was dropped with a downward facing pitch angle onto a sloping soil surface in order to create an induced forward acceleration in the airframe. The vertical impact velocity of the wing-box section was 349.2-in/s. A second objective of this project was to assess the capabilities of finite element simulations to predict the test responses. Finite element models of both fuselage sections were developed for execution in LS-DYNA(Registered Trademark), a commercial explicit nonlinear transient dynamic code. The models contained accurate representations of the airframe structure, the hat racks and hat rack masses, the floor and seat tracks, the luggage in the cargo hold for the forward section, and the detailed under-floor structure in the wing-box section. Initially, concentrated masses were used to represent the inertial properties of the seats, restraints, and ATD occupants. However, later simulations were performed that included finite element representations of the seats, restraints, and ATD occupants. These models were developed to more accurately replicate the seat loading of the floor and to enable prediction of occupant impact responses. Models were executed to generate analytical predictions of airframe responses, which were compared with test data to validate the model. Comparisons of predicted and experimental structural deformation and failures were made. Finally, predicted and experimental soil deformation and crater depths were also compared for both drop test configurations.

Jackson, Karen E.↗

High Fidelity Surface Charging and Magnetic Noise Analysis of the Juno Magnetometer

During Earth flyby of NASA’s Juno spacecraft, unexpected noise was observed in magnetometer data. The noise is attributed to surface currents sourced from ionospheric plasma and directed through the magnetometer boom structure by a vxB electric field. Approximate hand calculations under-predicted the severity of the noise by an order of magnitude. In response, a high fidelity analysis was performed to assess confidence in our model and risk to magnetometer science at Jupiter. Combining NASCAP2k with commercial FEA software, and using detailed inputs from a variety of environment models and CAD tools, the observed effect at Earth was replicated with agreement to a factor of 2. Extending the model to the Jovian environment, we predict a signal-to-noise ratio that is more favourable than at Earth and acceptable to magnetometer science.

Chinn, James↗

Modelling of the MEA float zone using accelerometer data

During a floating zone experiment involving the growth of indium on a recent orbiter mission, (STS 32) oscillation of the zone shapes were observed to occur in response to the background acceleration. An understanding of the nature of the response of the zone shape to forced (g-jitter) oscillations and predictions of its impact on future experiments is of great interest not only to the PI's but to other commercial and academic investigators who plan to fly similar experiments in the orbiter and on space station. Motivated by this, a 15 month study was undertaken to analyze the nature of the g-sensitivity of the STS 32 floating zone crystal growth experiment. Numerical models were used to describe the time-dependent free surface motion of the zone as it responds to the spacecraft residual acceleration. Relevant experimental data concerning the acceleration environment was obtained from the Honeywell in Space Accelerometer (HISA) investigators through MSFC's ACAP program and processed and analyzed. For the indium floating zone experiment, a series of calculations were made using time-dependent axial accelerations g(t). The form of g(t) included simple sinusoidal disturbances as well as actual data (subject to appropriate filtering) measured on the STS 32 mission. Focus was on the calculation of the response of the free surface of the zone as well as the internal flows and internal heat transfer. The influence of solidification on the response of the zone shape was also examined but found to be negligible.

Alexander, J. Iwan D.↗

Mercury's Internal Structure

We describe the current state of knowledge about Mercury's interior structure. We review the available observationalconstraints, including mass, size, density, gravity eld, spin state, composition, and tidal response. These data enablethe construction of models that represent the distribution of mass inside Mercury. In particular, we infer radial prolesof the pressure, density, and gravity in the core, mantle, and crust. We also examine Mercury's rotational dynamicsand the inuence of an inner core on the spin state and the determination of the moment of inertia. Finally, we discussthe wide-ranging implications of Mercury's internal structure on its thermal evolution, surface geology, capture in aunique spin-orbit resonance, and magnetic eld generation.

Mercury↗

Aerothermal Analysis of the Rocket Lab Venus Probe Heatshield

This document provides an overview of the aerothermodynamic analyses performed by the Aerothermodynamics Branch at NASA Langley Research Center for the Rocket Lab Venus Probe (RLVP). In addition to defining the baseline heating environment to the heatshield, this document pursues the experimental validation of key physical models at RLVP-relevant conditions. This experimental validation analysis, which captures the model form uncertainty, is used as one of two primary components of the margin assessment, where the other component is the parametric uncertainty. These model form (experimental) and parametric uncertainty components are used to construct a spatial and time varying margin for the heating to the RLVP heatshield. The margin is evaluated as the sum of the parametric and model form uncertainty components. The model form uncertainty is defined as the difference between the RLVP-relevant measurements and their simulations, using the upper limit uncertainty bounds for both the measurements and simulations in the comparisons. The differences in the dominant physics in the stagnation region and flank lead to the separate RLVP-relevant measurements for assessing the model form uncertainty in these two regions. These regions are addressed as follows: Stagnation Region Heating Environment: For the high-temperature stagnation-region, both the radiative heating and impact of blowing on convective heating are significant, while the impacts of turbulence and roughness are negligible. Coupled radiation and ablation LAURA/HARA solutions with ray-tracing provide the radiative heating over the entire vehicle, including the contributions from the Venus atmosphere and ablation species. Non-ablating LAURA simulations provide the convective heating. During the material-response computation typically used for TPS sizing, this non-ablating convective heating is corrected for the impact of ablation using the blowing correction. Coupled ablation LAURA simulations that capture finite-rate sur-face processes show that this blowing correction may be non-conservative over most of the heatshield. This non-conservatism is due to hydrogen recombination in the finite-rate surface model, which tends to increase the coupled ablation convective heating to near the non-ablating values, therefore making any reduction in the non-ablating value through the blowing correction non-conservative. This non-conservatism due to H catalysis is captured in the parametric component of the margin. The best available ground-test measurements that capture the impact of blowing on stagnation region convective heating, at RLVP-relevant conditions, indicate that the current blowing reduction model is non-conservative by up to 20% at RLVP-relevant blowing rates (the coupled blowing simulations were also non-conservative). Because of the relatively low velocity of the ground tests and the non-Venus atmospheric chemistry, these measurements do not capture the chemistry and therefore do not inform the uncertainty due to H catalysis. However, they do capture the fluid mechanics of blowing. The non-conservatism of the blowing correction implied by these measurements is covered by the model form component of the margin, which leads to total margin values over 50%. For the radiative heating, the shock-tube informed bias approach suggests a model form uncertainty of roughly 20%, while the parametric uncertainty analysis suggests values over 100%. The combined stagnation-point radiation margin of over 100% leads to peak margined radiative heating values of over300 W/cm2, which remains small relative to the peak margined convective heating of nearly 2000 W/cm2. Based on this analysis, at the stagnation point, the peak margined heat rate is 2203 W/cm2 and the margined total heat load is 31.5 kJ/cm2 for the current nominal trajectory. Flank Heating Environment: The forebody flank (and near-shoulder) heating environment is dominated by the impact of turbulence, roughness augmentation, and ablation on the convective heating. An extensive collection of ground test measurements with RLVP-relevant turbulence and roughness is studied to show that the maximum difference between the simulated and measured convective heating is 5%. However, with the exception of the Holden measurements from the 1980s, these measurements do not include roughness elements extending into the supersonic region of the boundary layer, which is likely to occur for RLVP (due to the 45 degree sphere-cone geometry). The interaction between the supersonic flow and roughness could cause convective heating augmentation fundamentally different than for locally subsonic flow. Although these Holden measurements are consistent with the other measurements considered, another path was pursued to assure that the rough-ness height extending into supersonic flow does not fundamentally change the roughness augmentation. This additional path was a computational effort to resolve the roughness elements in the CFD grid, so that the interaction be-tween the roughness elements and locally supersonic flow may be simulated in detail. This roughness-resolved CFD simulation is feasible because of the RLVP forebody TPS’s patterned roughness, which may be approximated analytically, and because of the axisymmetric nominal flow field, which allows a narrow surface region to be simulated and therefore make the computational expense feasible. These grid-resolved roughness simulations, which are performed at actual RLVP flight conditions, result in heating augmentation values that are below the design approach for roughness augmentation. This provides evidence that the design approach for RLVP roughness augmentation is sufficient. Based on this analysis, at this flank or near-shoulder location, the peak margined total heat rate is 2088 W/cm2and the margined total heat load is 26.0 kJ/cm2for the current nominal trajectory. Heat flux, shear, pressure and heat transfer coefficient at the RLVP stagnation point and near shoulder location are evaluated for the entire trajectory, and curved fit to a functional form of F=AρB∞UC∞. These simplified relationships for the nominal and margined aerothermal environments are referred to as aerothermal indicators, and presented at the end of this document.

Christopher O Johnston↗

A Large Ensemble Global Dataset for Climate Impact Assessments

We present a self-consistent, large ensemble, high-resolution global dataset of long-term future climate, which accounts for the uncertainty in climate system response to anthropogenic emissions of greenhouse gases and in geographical patterns of climate change. The dataset is developed by applying an integrated spatial disaggregation (SD) - bias-correction (BC) method to climate projections from the MIT Integrated Global System Model (IGSM). Four emission scenarios are considered that represent energy and environmental policies and commitments of potential future pathways, namely, Reference, Paris Forever, Paris 2 °C and Paris 1.5 °C. The dataset contains nine key meteorological variables on a monthly scale from 2021 to 2100 at a spatial resolution of 0.5°x 0.5°, including precipitation, air temperature (mean, minimum and maximum), near-surface wind speed, shortwave and longwave radiation, specific humidity, and relative humidity. We demonstrate the dataset’s ability to represent climate-change responses across various regions of the globe. This dataset can be used to support regional-scale climate-related impact assessments of risk across different applications that include hydropower, water resources, ecosystem, agriculture, and sustainable development.

54 ENVIRONMENTAL SCIENCES↗

Hypersonic Second Mode Instability Response to Shaped Roughness

An experimental campaign was conducted on a 7-degree half-angle cone in the NASA Langley Research Center 20-Inch Mach 6 Wind Tunnel to examine the influence of arrays of regularly spaced roughness elements on instability growth and transition. The primary element shape was a pair of elliptical planform ramps that were inclined at equal and opposite angles with respect to the local streamwise direction. The element shapes were designed to induce transient growth disturbances that would lead to sustained azimuthal modulation of the boundary layer flow while limiting the nearfield disturbances to avoid an immediate, i.e., effective tripping of the boundary layer. The bulk of the run matrix consisted of testing different element height sat free stream unit Reynolds numbers ranging from 9.8 to 13.1 million per meter. Other element shapes previously designed for tripping hypersonic boundary layers were also implemented. The model was instrumented with surface mounted Kulite ® and PCB ® pressure transducers and thermocouples. Spectra from the PCBs ® indicated clear suppression of the second-mode instability; however, neither the PCB ® spectra nor the heat transfer data presented strong evidence for delayed turbulent flow. Complementary stability computations likewise demonstrated second-mode reduction, particularly just downstream of the roughness, but also revealed a rise in first mode (streak-instability) amplitudes from the baseline that was likely responsible for the earlier transition observed for taller roughness cases.

Hypersonics↗

Hypersonic Second-Mode Instability Response to Shaped Roughness

An experimental campaign was conducted on a 7-degree half-angle cone in the NASA Langley Research Center 20-Inch Mach 6 Wind Tunnel to examine the influence of arrays of regularly spaced roughness elements on instability growth and transition. The primary element shape was a pair of elliptical planform ramps that were inclined at equal and opposite angles with respect to the local streamwise direction. The element shapes were designed to induce transient growth disturbances that would lead to sustained azimuthal modulation of the boundary layer flow while limiting the nearfield disturbances to avoid an immediate, i.e., effective tripping of the boundary layer. The bulk of the run matrix consisted of testing different element height sat free stream unit Reynolds numbers ranging from 9.8 to 13.1 million per meter. Other element shapes previously designed for tripping hypersonic boundary layers were also implemented. The model was instrumented with surface mounted Kulite ® and PCB ® pressure transducers and thermocouples. Spectra from the PCBs ® indicated clear suppression of the second-mode instability; however, neither the PCB ® spectra nor the heat transfer data presented strong evidence for delayed turbulent flow. Complementary stability computations likewise demonstrated second-mode reduction, particularly just downstream of the roughness, but also revealed a rise in first mode (streak-instability) amplitudes from the baseline that was likely responsible for the earlier transition observed for taller roughness cases.

Hypersonics↗

Hypersonic Second-Mode Instability Response to Shaped Roughness

An experimental campaign was conducted on a 7-degree half-angle cone in the NASA Langley Research Center 20-Inch Mach 6 Wind Tunnel to examine the influence of arrays of regularly spaced roughness elements on instability growth and transition. The primary element shape was a pair of elliptical planform ramps that were inclined at equal and opposite angles with respect to the local streamwise direction. The element shapes were designed to induce transient growth disturbances that would lead to sustained azimuthal modulation of the boundary layer flow while limiting the nearfield disturbances to avoid an immediate, i.e., effective tripping of the boundary layer. The bulk of the run matrix consisted of testing different element height sat free stream unit Reynolds numbers ranging from 9.8 to 13.1 million per meter. Other element shapes previously designed for tripping hypersonic boundary layers were also implemented. The model was instrumented with surface mounted Kulite ® and PCB ® pressure transducers and thermocouples. Spectra from the PCBs ® indicated clear suppression of the second-mode instability; however, neither the PCB ® spectra nor the heat transfer data presented strong evidence for delayed turbulent flow. Complementary stability computations likewise demonstrated second-mode reduction, particularly just downstream of the roughness, but also revealed a rise in first mode (streak-instability) amplitudes from the baseline that was likely responsible for the earlier transition observed for taller roughness cases.

Hypersonics↗

Biosphere/atmosphere CO2 exchange in tundra ecosystems - Community characteristics and relationships with multispectral surface reflectance

CO2 exchange rates were measured at selected tundra sites near Bethel, Alaska using portable, climate-controlled, instrumented enclosures. The empirically modeled exchange rate for a representative area of vegetated tundra was 1.2 +/- 1.2 g/sq m/d, compared to a tower-measured exchange over the same time period of 1.1 +.0- 1.2 g/sq m/d. Net exchange in response to varying light levels was compared to wet meadow and dry upland tundra, and to the net exchange measured by the micrometeoroidal tower technique. The multispectral reflectance properties of the sites were measured and related to exchange rates in order to provide a quantitative foundation for the use of satellite remote sensing to monitor biosphere/atmosphere CO2 exchange in the tundra biome.

Whiting, Gary J.↗

ANALYSIS OF THE MSL/MEDLI ENTRY DATA WITH COUPLED CFD AND MATERIAL RESPONSE.

The Mars Science Laboratory (MSL) was protected during its atmospheric entry by an instrumented heat-shield using NASA's Phenolic Impregnated Carbon Ablator (PICA) material. PICA is a lightweight carbon fiber/polymeric resin material that offers out-standing performances for protecting probes during planetary entry. The Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of material response and atmospheric entry. MEDLI recorded, among other things, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP). The objective of this work is to showcase and analyze the coupling between the material response and the aerothermal environment. As shown in Figure 1, the workflow is divided into the following steps. First, the aerothermal properties are computed in the Data Parallel Line Relaxation (DPLR) code [3] and used with the Nonequilibrium air radiation (NEQAIR) program [8] to compute radiative heating. Second, the thermal response inside the material is computed in the Porous material Analysis Toolbox based on Open-FOAM (PATO) using a fixed blowing correction parameter. Third, the pyrolysis gases computed in PATO are used as inputs to a blowing boundary condition within DPLR. Fourth, the new environment properties from DPLR are used in NEQAIR to provide an updated solution, then both the updated aerothermal environment and radiative heating are used in PATO without blowing correction. The third and fourth steps are then repeated until convergence in surface temperature is obtained. Convergence in the radiative heating is generally achieved before surface temperature, at which point the radiative heating is no longer updated. Char mass loss rates are forced to zero to produce a non-receding surface condition. For early time points in the trajectory, where flow around the MSL aeroshell is rarefied, the Direct Simulation Monte Carlo (DSMC) code, SPARTA, is used to compute the aerothermal environment. Iteration between PATO and SPARTA is not performed due to the computational cost of DSMC simulations. Preliminary results of the coupling between PATO and DPLR for the MSL heatshield atmospheric entry model are presented in Figures 2-4 at 65 seconds after entry interface. Figure 2 shows the surface temperature results from an uncoupled simulation in PATO with the blowing correction parameter applied (left) along with the coupled surface temperature after iteration (right). Figure 3 shows the surface temperature along the centerline from windward to leeward for easier comparison. Figure 4 shows the coupled and uncoupled pyrolysis gas blowing rate. Mars 2020 used a similar heatshield consisting of PICA for thermal protection during entry, descent, and landing. In preparation for Mars 2020 post-flight analysis, the predictive material response capability is benchmarked against flight data from MEDLI. This work represents an important milestone toward the development of validated predictive capabilities for designing thermal protection systems for planetary probes.

Mars Science Laboratory↗

Analysis of MSL/MEDLI Entry Data with Coupled CFD and Material Response

The Mars Science Laboratory (MSL) was protected during its atmospheric entry by an instrumented heatshield using NASA's Phenolic Impregnated Carbon Ablator (PICA) material [1]. PICA is a lightweight carbon fiber/polymeric resin material that offers outstanding performances for protecting probes during planetary entry. The Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of material response and atmospheric entry. MEDLI recorded, among other things, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP) [2]. The objective of this work is to showcase and analyze the coupling between the material response and the aerothermal environment. As shown in Figure 1, the workflow is divided into the following steps. First, the aerothermal properties are computed in the Data Parallel Line Relaxation (DPLR) code [3] and used with the Nonequilibrium air radiation (NEQAIR) program [8] to compute radiative heating. Second, the thermal response inside the material is computed in the Porous material Analysis Toolbox based on OpenFOAM (PATO) [4,5,6] using a fixed blowing correction parameter. Third, the pyrolysis gases computed in PATO are used as inputs to a blowing boundary condition within DPLR. Fourth, the new environment properties from DPLR are used in NEQAIR to provide an updated solution, then both the updated aerothermal environment and radiative heating are used in PATO without blowing correction. The third and fourth steps are then repeated until convergence in surface temperature is obtained. Convergence in the radiative heating is generally achieved before surface temperature, at which point the radiative heating is no longer updated. Char mass loss rates are forced to zero to produce a non-receding surface condition. For early time points in the trajectory, where flow around the MSL aeroshell is rarefied, the Direct Simulation Monte Carlo (DSMC) code, SPARTA [7], is used to compute the aerothermal environment. Iteration between PATO and SPARTA is not performed due to the computational cost of DSMC simulations. Preliminary results of the coupling between PATO and DPLR for the MSL heatshield atmospheric entry model are presented in Figures 2-4 at 65 seconds after entry interface. Figure 2 shows the surface temperature results from an uncoupled simulation in PATO with the blowing correction parameter applied (left) along with the coupled surface temperature after iteration (right). Figure 3 shows the surface temperature along the centerline from windward to leeward for easier comparison. Figure 4 shows the coupled and uncoupled pyrolysis gas blowing rate. Mars 2020 used a similar heatshield consisting of PICA for thermal protection during entry, descent, and landing. In preparation for Mars 2020 post-flight analysis, the predictive material response capability is benchmarked against flight data from MEDLI. This work represents an important milestone toward the development of validated predictive capabilities for designing thermal protection systems for planetary probes.

Thermal Protection Systems↗

Sea-surface temperature pattern effects have slowed global warming and biased warming-based constraints on climate sensitivity

The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR)—key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO 2 forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections.

58 GEOSCIENCES↗

Section on Observed Impacts on El Nino

Agricultural applications of El Nino forecasts are already underway in some countries and need to be evaluated or re-evaluated. For example, in Peru, El Nino forecasts have been incorporated into national planning for the agricultural sector, and areas planted with rice and cotton (cotton being the more drought-tolerant crop) are adjusted accordingly. How well are this and other such programs working? Such evaluations will contribute to the governmental and intergovernmental institutions, including the Inter-American Institute for Global Change Research and the US National Ocean and Atmospheric Agency that are fostering programs to aid the effective use of forecasts. As El Nino climate forecasting grows out of the research mode into operational mode, the research focus shifts to include the design of appropriate modes of utilization. Awareness of and sensitivity to the costs of prediction errors also grow. For example, one major forecasting model failed to predict the very large El Nino event of 1997, when Pacific sea-surface temperatures were the highest on record. Although simple correlations between El Nino events and crop yields may be suggestive, more sophisticated work is needed to understand the subtleties of the interplay among the global climate system, regional climate patterns, and local agricultural systems. Honesty about the limitations of an forecast is essential, especially when human livelihoods are at stake. An end-to-end analysis links tools and expertise from the full sequence of ENSO cause-and-effect processes. Representatives from many disciplines are needed to achieve insights, e.g, oceanographers and atmospheric scientists who predict El Nino events, climatologists who drive global climate models with sea-surface temperature predictions, agronomists who translate regional climate connections in to crop yield forecasts, and economists who analyze market adjustments to the vagaries of climate and determine the value of climate forecasts. Methods include historical studies to understand past patterns and to test hindcasts of the prediction tools, crop modeling, spatial analysis and remote sensing. This research involves expanding, deepening, and applying the understanding of physical climate to the fields of agronomy and social science; and the reciprocal understanding of crop growth and farm economics to climatology. Delivery of a regional climate forecast with no information about how the climate forecast was derived limits its effectiveness. Explanation of a region's major climate driving forces helps to place a seasonal forecast in context. Then, a useful approach is to show historical responses to previous El Nino events, and projections, with uncertainty intervals, of crop response from dynamic process crop growth models. Regional ID forecasts should be updated with real-time weather conditions. Since every El Nino event is different, it is important to track, report and advise on each new event as it unfolds. The stability of human enterprises depends on understanding both the potentialities and the limits of predictability. Farmers rely on past experience to anticipate and respond to fluctuations in the biophysical systems on which their livelihoods depend. Now scientists are improving their ability to predict some major elements of climate variability. The improvements in the reliability of El Nino forecasts are encouraging, but seasonal forecasts for agriculture are not, and will probably never be completely infallible, due to the chaotic nature of the climate system. Uncertainties proliferate as we extend beyond Pacific sea-surface temperatures to climate teleconnections and agricultural outcomes. The goal of this research is to shed as a clear light as possible on these inherent uncertainties and thus to contribute to the development of appropriate responses to El Nino and other seasonal forecasts for a range of stakeholders, which, ultimately, includes food consumers everywhere.

Rosenzweig, Cynthia↗

Bridging Nano- and Microscale X-Ray Tomography for Battery Research by Leveraging Artificial Intelligence

X-ray computed tomography (CT) is a non-destructive imaging technique in which contrast originates from the materials' absorption coefficient. The recent development of laboratory nanoscale CT (nano-CT) systems has pushed the spatial resolution for battery material imaging to voxel sizes of 50 nm, a limit previously achievable only with synchrotron facilities. Given the non-destructive nature of CT, in situ and operando studies have emerged as powerful methods to quantify morphological parameters, such as tortuosity factor, porosity, surface area and volume expansion, during battery operation or cycling. Combined with artificial intelligence and machine learning analysis techniques, nano-CT has enabled the development of predictive models to analyse the impact of the electrode microstructure on cell performances or the influence of material heterogeneities on electrochemical responses. In this Review, we discuss the role of X-ray CT and nano-CT experimentation in the battery field, discuss the incorporation of artificial intelligence and machine learning analyses and provide a perspective on how the combination of multiscale CT imaging techniques can expand the development of predictive multiscale battery behavioural models.

diagnostics↗

Cycles till failure of silver-zinc cells with competing failure modes - Preliminary data analysis

The data analysis of cycles to failure of silver-zinc electrochemical cells with competing failure modes is presented. The test ran 129 cells through charge-discharge cycles until failure; preliminary data analysis consisted of response surface estimate of life. Batteries fail through low voltage condition and an internal shorting condition; a competing failure modes analysis was made using maximum likelihood estimation for the extreme value life distribution. Extensive residual plotting and probability plotting were used to verify data quality and selection of model.

Sidik, S. M.↗