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At least 343 records · Page 19

SPS-ALPHA: The First Practical Solar Power Satellite via Arbitrarily Large Phased Array

The vision of delivering solar power to Earth from platforms in space has been known for decades. However, early architectures to accomplish this vision were technically complex and unlikely to prove economically viable. Some of the issues with these earlier solar power satellite (SPS) concepts – particularly involving technical feasibility – were addressed by NASA’s space solar power (SSP) studies and technology research in the mid-to-late 1990s. Despite that progress, ten years ago a number of key technical and economic uncertainties remained. A new SPS concept has been proposed that resolves many, if not all, of those uncertainties: “SPSALPHA” (Solar Power Satellite by means of Arbitrarily Large Phased Array). During 2011-2012 the NASA Innovative Advanced Concepts (NIAC) Program supported a Phase 1 “SPS-ALPHA” project, the goal of which was to establish the technical and economic viability of the SPS-ALPHA concept to an early TRL 3 – analytical proof-of-concept – and provide a framework for further study and technology development. The objectives of this project were to: (1) conduct an initial end-to-end systems analysis of the SPS-ALPHA concept in order to determine its technical feasibility; (2) identify and assess in greater detail the key technology challenges inherent in the architecture (including figures of merit for each critical technology area); (3) conduct an initial evaluation of the economic viability of the concept (as a function of key performance parameters); and, (4) define a preliminary roadmap for the further development of the SPS-ALPHA concept.

Mankins, John↗

Advancing Satellite-Constrained Modeled Air-Sea CO 2 Fluxes With a Focus on the Strength of the Southern Ocean Carbon Sink

Challenge and Motivation: The ocean plays a critical role in mitigating climate change by removing approximately a quarter of annual anthropogenic CO 2 emissions from the atmosphere. Model-based estimates point to the Southern Ocean as a key marine region, responsible for approximately 40 % of the anthropogenic carbon uptake by the global ocean. However, the contemporary strength of the Southern Ocean carbon sink has recently come into question. On the one hand, airborne-based observations of atmospheric CO 2 gradients indicate that the Southern Ocean represents a strong net sink of atmospheric CO 2 , consistent in magnitude with atmospheric inversion estimates and surface-ocean partial pressure of CO 2 (pCO 2 )-based products. On the other hand, estimates of pCO 2 based on in situ pH measurements taken by biogeochemical profiling floats yield strong wintertime outgassing fluxes that greatly reduce the Southern Ocean’s annually integrated CO 2 uptake. This uncertainty in the strength of the Southern Ocean air-sea CO 2 flux and its role in the global carbon cycle hinders our ability to constrain global carbon fluxes, one of the major goals of NASA’s Carbon Monitoring System (CMS). Opportunity: The NASA Ocean Biogeochemical Model (NOBM) produces near-global pCO 2 and air-sea CO 2 flux estimates that are currently included into the NASA’s Goddard Earth Observing System (GEOS) models in support of the CMS effort to monitor global carbon fluxes. The NOBM assimilates ocean color data to improve the representation of biogeochemical fluxes and overcome spatial and temporal gaps in the space-based retrievals. Here, we propose to advance the satellite-constrained flux estimates by investigating the uncertainties in the Southern Ocean air-sea CO 2 flux produced by the NOBM, and assess the value that remote sensing ocean color data can have in providing improved estimates of carbon fluxes in the ocean. Our proposed work includes the delivery of refined in situ float-based carbon fluxes to serve as a constraint on the model-based estimates. Taking advantage of the model’s integration of satellite ocean color data to represent multiple phytoplankton groups, we propose to deliver maps of biogenic carbon export specific to each modeled phytoplankton type and investigate the role of ecological plankton complexity in regulating marine carbon uptake and export. Goals: (a) Delivery of seasonally-adjusted float-based Southern Ocean air-sea CO 2 fluxes: We will produce updated and improved float-based air-sea CO 2 fluxes that will serve as a bias-reduced float-based constraint to evaluate our model-based estimates of the NOBM. (b) Investigation of uncertainties in Southern Ocean air-sea CO 2 flux from the NOBM: Modeled air-sea carbon fluxes will be evaluated against the updated float product as well as ship- and airborne-based data to identify uncertainties and potential model deficiencies. (c) Delivery of model-based carbon export partitioning by phytoplankton functional types (PFTs): We will produce depth-resolved maps of particulate organic export production integrated for all phytoplankton groups and allocated to each individual PFT in the model. The expected significance of this goal is to quantify the role that the functional-oriented diversity in phytoplankton groups represented in the NOBM plays in regulating air-sea CO 2 fluxes in the Southern Ocean.

Lionel A. Arteaga↗

Additively Manufactured Wind Tunnel Balances for Propulsive Force Measurement

Propulsive forces and moments during powered descent are not understood well enough to design an entry, decent, and landing vehicle with high confidence using solely computational fluid dynamics modelling (CFD). Therefore, wind tunnel testing is required to quantify uncertainties in computational modeling and simulation. Wind tunnel balances are structural, high-precision, multi-axis force transducers that provide direct measurement of these aerodynamic forces and moments, however their complex designs make them costly and time consuming to produce and approaches used to manufacture them have not changed significantly since the 1960s. This work demonstrates that additive manufacturing (AM) can be used to manufacture wind tunnel balances with significantly reduced fabrication time and expense. Moreover, the design flexibility afforded by the additive manufacturing process has the potential to enable new capabilities with respect to measuring propulsion forces during entry, decent, and landing testing. Here we present two novel balance designs enabled by AM. One will provide direct measurement of aerodynamic interference forces and moments on powered descent models (retropropulsion forces) to support CFD validation and further development of Mars human landing vehicle concepts. The second design will be used to characterize a reaction control system during entry descent and landing testing over a wide Mach number range.

Wind tunnel balance↗

Additively Manufactured Balances for Propulsive Force Measurement

Propulsive forces and moments during powered descent are not understood well enough to design an entry, decent, and landing vehicle with high confidence using solely computational fluid dynamics modelling (CFD). Therefore, wind tunnel testing is required to quantify uncertainties in computational modeling and simulation. Wind tunnel balances are structural, high-precision, multi-axis force transducers that provide direct measurement of these aerodynamic forces and moments, however their complex designs make them costly and time consuming to produce and approaches used to manufacture them have not changed significantly since the 1960s. This work demonstrates that additive manufacturing (AM) can be used to manufacture wind tunnel balances with significantly reduced fabrication time and expense. Moreover, the design flexibility afforded by the additive manufacturing process has the potential to enable new capabilities with respect to measuring propulsion forces during entry, decent, and landing testing. Here we present two novel balance designs enabled by AM. One will provide direct measurement of aerodynamic interference forces and moments on powered descent models (retropropulsion forces) to support CFD validation and further development of Mars human landing vehicle concepts. The second design will be used to characterize a reaction control system during entry decent and landing testing over a wide Mach number range.

Wind tunnel balance↗

BioSentinel: Mission Summary and Lessons Learned From the First Deep Space Biology CubeSat Mission

Launched on Artemis-1, BioSentinel carries a biology experiment into deep space for the first time in 50 years. A 6U CubeSat form factor was utilized for the spacecraft which included technologies newly developed or adapted for operations beyond Earth orbit. The spacecraft carries onboard budding yeast, Saccharomyces cerevisiae, as an analog to human cells to test the biological response to deep space radiation. This was the maiden deep-space voyage for many of the subsystems, and the first time to evaluate their performance in flight operation. Flying a CubeSat beyond LEO comes with unique challenges with respect to trajectory uncertainty and mission operations planning. The nominal plan was a lunar fly-by, followed by an insertion into Heliocentric orbit. However, some possible scenarios included lunar eclipses that could have severely impacted the power budget during that phase of the mission, while others could have resulted in a “Retrograde” hyperbola at swing-by resulting in the spacecraft traveling inward toward Earth or even towards a collision with the lunar surface. The commissioning phase of the mission was successful and completed a week ahead of schedule. It did not come without its exciting moments and challenges. First contact with the spacecraft uncovered that the vehicle was unexpectedly tumbling after deployment, a situation that needed to be corrected urgently. The mission operations team executed a contingency plan to stabilize the spacecraft, with just moments to spare before the battery ran out of power. The BioSensor payload onboard the spacecraft is a complex instrument that includes microfluidics, fluid systems, sensor control electronics, as well at the living yeast cells. BioSentinel also included a TimePix radiation sensor implemented by JSC’s RadWorks group. Dose and Linear Energy Transfer (LET) data is compared directly to the rate of DSB-and repair events measured by the S. cerevisiae cells. BioSentinel mature nanosatellite technologies included: deep space communications and navigation, autonomous attitude control and momentum management, and micro-propulsion systems, to provide an adaptable nanosatellite platform for deep space uses. This paper discusses the performance of the BioSentinel spacecraft through the mission phase, and includes lessons learned from challenges and anomalies. BioSentinel had many successes and will be a pathfinder for future deep space CubeSats and biology missions.

BioSentinel↗

Biosentinel: Mission Summary and Lessons Learned From the First Deep Space Biology CubeSat Mission

Launched on Artemis-1, BioSentinel carries a biology experiment into deep space for the first time in 50 years. A 6U CubeSat form factor was utilized for the spacecraft which included technologies newly developed or adapted for operations beyond Earth orbit. The spacecraft carries onboard budding yeast, Saccharomyces cerevisiae, as an analog to human cells to test the biological response to deep space radiation. This was the maiden deep-space voyage for many of the subsystems, and the first time to evaluate their performance in flight operation. Flying a CubeSat beyond LEO comes with unique challenges with respect to trajectory uncertainty and mission operations planning. The nominal plan was a lunar fly-by, followed by an insertion into Heliocentric orbit. However, some possible scenarios included lunar eclipses that could have severely impacted the power budget during that phase of the mission, while others could have resulted in a “Retrograde” hyperbola at swing-by resulting in the spacecraft traveling inward toward Earth or even towards a collision with the lunar surface. The commissioning phase of the mission was successful and completed a week ahead of schedule. It did not come without its exciting moments and challenges. First contact with the spacecraft uncovered that the vehicle was unexpectedly tumbling after deployment, a situation that needed to be corrected urgently. The mission operations team executed a contingency plan to stabilize the spacecraft, with just moments to spare before the battery ran out of power. The BioSensor payload onboard the spacecraft is a complex instrument that includes microfluidics, fluid systems, sensor control electronics, as well at the living yeast cells. BioSentinel also included a TimePix radiation sensor implemented by JSC’s RadWorks group. Dose and Linear Energy Transfer (LET) data is compared directly to the rate of DSB-and repair events measured by the S. cerevisiae cells. BioSentinel mature nanosatellite technologies included: deep space communications and navigation, autonomous attitude control and momentum management, and micro-propulsion systems, to provide an adaptable nanosatellite platform for deep space uses. This paper discusses the performance of the BioSentinel spacecraft through the mission phase, and includes lessons learned from challenges and anomalies. BioSentinel had many successes and will be a pathfinder for future deep space CubeSats and biology missions.

BioSentinel↗

Biosentinel: The First Deep Space Biology CubeSat Mission- Mission Summary and Lessons Learned

Launched on Artemis-1, BioSentinel carries a biology experiment into deep space for the first time in 50 years. A 6U CubeSat form factor was utilized for the spacecraft which included technologies newly developed or adapted for operations beyond Earth orbit. The spacecraft carries onboard budding yeast, Saccharomyces cerevisiae, as an analog to human cells to test the biological response to deep space radiation. This was the maiden deep-space voyage for many of the subsystems, and the first time to evaluate their performance in flight operation. Flying a CubeSat beyond LEO comes with unique challenges with respect to trajectory uncertainty and mission operations planning. The nominal plan was a lunar fly-by, followed by an insertion into Heliocentric orbit. However, some possible scenarios included lunar eclipses that could have severely impacted the power budget during that phase of the mission, while others could have resulted in a “Retrograde” hyperbola at swing-by resulting in the spacecraft traveling inward toward Earth or even towards a collision with the lunar surface. The commissioning phase of the mission was successful and completed a week ahead of schedule. It did not come without its exciting moments and challenges. First contact with the spacecraft uncovered that the vehicle was unexpectedly tumbling after deployment, a situation that needed to be corrected urgently. The mission operations team executed a contingency plan to stabilize the spacecraft, with just moments to spare before the battery ran out of power. The BioSensor payload onboard the spacecraft is a complex instrument that includes microfluidics, fluid systems, sensor control electronics, as well at the living yeast cells. BioSentinel also included a TimePix radiation sensor implemented by JSC’s RadWorks group. Dose and Linear Energy Transfer (LET) data is compared directly to the rate of DSB-and repair events measured by the S. cerevisiae cells. BioSentinel mature nanosatellite technologies included: deep space communications and navigation, autonomous attitude control and momentum management, and micro-propulsion systems, to provide an adaptable nanosatellite platform for deep space uses. This paper discusses the performance of the BioSentinel spacecraft through the mission phase, and includes lessons learned from challenges and anomalies. BioSentinel had many successes and will be a pathfinder for future deep space CubeSats and biology missions.

BioSentinel↗

Uncertainty in Heart Rate Complexity Metrics Caused by R-Peak Perturbations

Heart rate complexity (HRC) is a proven metric for gaining insight into human stress and physiological deterioration. To calculate HRC, the detection of the exact instance of when the heart beats, the R-peak, is necessary. Electrocardiogram (ECG) signals can often be corrupted by environmental noise (e.g., from electromagnetic interference, movement artifacts), which can potentially alter the HRC measurement, producing erroneous inputs which feed into decision support models. Current literature has only investigated how HRC is affected by noise when R-peak detection errors occur (false positives and false negatives). However, the numerical methods used to calculate HRC are also sensitive to the specific location of the fiducial point of the R-peak. This raises many questions regarding how this fiducial point is altered by noise, the resulting impact on the measured HRC, and how we can account for noisy HRC measures as inputs into our decision models. This work uses Monte Carlo simulations to systematically add white and pink noise at different permutations of signal-to-noise ratios (SNRs), time segments, sampling rates, and HRC measurements to characterize the influence of noise on the HRC measure by altering the fiducial point of the R-peak. Using the generated information from these simulations provides improved decision processes for system design which address key concerns such as permutation entropy being a more precise, reliable, less biased, and more sensitive measurement for HRC than sample and approximate entropy.

Napoli, Nicholas J.↗

Comparing Consider-Covariance Analysis with Sigma-Point Consider Filter and Linear-Theory Consider Filter Formulations

Recent literature in applied estimation theory reflects growing interest in the sigma-point (also called unscented ) formulation for optimal sequential state estimation, often describing performance comparisons with extended Kalman filters as applied to specific dynamical problems [c.f. 1, 2, 3]. Favorable attributes of sigma-point filters are described as including a lower expected error for nonlinear even non-differentiable dynamical systems, and a straightforward formulation not requiring derivation or implementation of any partial derivative Jacobian matrices. These attributes are particularly attractive, e.g. in terms of enabling simplified code architecture and streamlined testing, in the formulation of estimators for nonlinear spaceflight mechanics systems, such as filter software onboard deep-space robotic spacecraft. As presented in [4], the Sigma-Point Consider Filter (SPCF) algorithm extends the sigma-point filter algorithm to the problem of consider covariance analysis. Considering parameters in a dynamical system, while estimating its state, provides an upper bound on the estimated state covariance, which is viewed as a conservative approach to designing estimators for problems of general guidance, navigation and control. This is because, whether a parameter in the system model is observable or not, error in the knowledge of the value of a non-estimated parameter will increase the actual uncertainty of the estimated state of the system beyond the level formally indicated by the covariance of an estimator that neglects errors or uncertainty in that parameter. The equations for SPCF covariance evolution are obtained in a fashion similar to the derivation approach taken with standard (i.e. linearized or extended) consider parameterized Kalman filters (c.f. [5]). While in [4] the SPCF and linear-theory consider filter (LTCF) were applied to an illustrative linear dynamics/linear measurement problem, in the present work examines the SPCF as applied to nonlinear sequential consider covariance analysis, i.e. in the presence of nonlinear dynamics and nonlinear measurements. A simple SPCF for orbit determination, exemplifying an algorithm hosted in the guidance, navigation and control (GN&C) computer processor of a hypothetical robotic spacecraft, was implemented, and compared with an identically-parameterized (standard) extended, consider-parameterized Kalman filter. The onboard filtering scenario examined is a hypothetical spacecraft orbit about a small natural body with imperfectly-known mass. The formulations, relative complexities, and performances of the filters are compared and discussed.

Lisano, Michael E.↗

Materials and Process Activities for NASA's Composite Crew Module

In January 2007, the NASA Administrator and Associate Administrator for the Exploration Systems Mission Directorate chartered the NASA Engineering and Safety Center (NESC) to design, build, and test a full-scale Composite Crew Module (CCM). The overall goal of the CCM project was to develop a team from the NASA family with hands-on experience in composite design, manufacturing, and testing in anticipation of future space exploration systems being made of composite materials. The CCM project was planned to run concurrently with the Orion project s baseline metallic design within the Constellation Program so that features could be compared and discussed without inducing risk to the overall Program. The materials and process activities were prioritized based on a rapid prototype approach. This approach focused developmental activities on design details with greater risk and uncertainty, such as out-of-autoclave joining, over some of the more traditional lamina and laminate building block levels. While process development and associated building block testing were performed, several anomalies were still observed at the full-scale level due to interactions between process robustness and manufacturing scale-up. This paper describes the process anomalies that were encountered during the CCM development and the subsequent root cause investigations that led to the final design solutions. These investigations highlight the importance of full-scale developmental work early in the schedule of a complex composite design/build project.

Polis, Daniel L.↗

An Investigation of Flight Deck Data Link in the Terminal Area

The Next Generation Air Transportation System (NextGen) and Europe's Single European Sky ATM Research (SESAR) concepts require an increased use of trajectory-based operations, including extensive strategic air traffic control clearances. The clearances are lengthy and complex, which necessitate data link communications to allow for message permanence and integration into the autoflight systems (i.e., autoload capability). This paper examines the use of flight deck data link communications for strategic and tactical clearance usage in the terminal area. A human-in-the-loop simulation was conducted using a high-fidelity flight deck simulator, with ten commercial flight crews as participants. Data were collected from six flight scenarios in the San Francisco terminal airspace. The variables of interest were ATC message modality (voice v. data link), temporal quality of the message (tactical v. strategic) and message length. Dependent variables were message response times, communication clarifications, communication-related errors, and pilot workload. Response time results were longer in data link compared to voice, a finding that has been consistently revealed in a number of other simulations [1]. In addition, strategic clearances and longer messages resulted in a greater number of clarifications and errors, suggesting an increase in uncertainty of message interpretation for the flight crews when compared to tactical clearances. The implications for strategic and compound clearance usage in NextGen and SESAR are discussed

data link communication↗

A methodology for the synthesis of robust feedback systems

A new methodology is developed for the synthesis of linear, time-variant (LTI) controllers for multivariable LTI systems. The resulting closed-loop system is nominally stable and exhibits a known level of performance. In addition, robustness of the feedback system is guaranteed, i.e., stability and performance are retained in the presence of multiple unstructured uncertainty blocks located at various points in the feedback loop. The design technique is referred to as the Causality Recovery Methodology (CRM). The CRM relies on the Youla parameterization of all stabilizing compensators to ensure nominal stability of the feedback system. A frequency-domain inequality in terms of the structured singular value mu defines the robustness specification. The optimal compensator, with respect to the mu condition, is shown to be noncausal in general. The aim of the CRM is to find a stable, causal transfer function matrix that approximates the robustness characteristics of the optimal solution. The CRM, via a series of infinite-dimensional convex programs, produces a closed-loop system whose performance robustness is at least as good as that of any initial design. The algorithm is approximated by a finite dimensional process for the purposes of implementation. Two numerical examples confirm the potential viability of the CRM concept; however, the robustness improvement comes at the expense of increased computational burden and compensator complexity.

Milich, David Albert↗

Quality metrics for sensor images

Methods are needed for evaluating the quality of augmented visual displays (AVID). Computational quality metrics will help summarize, interpolate, and extrapolate the results of human performance tests with displays. The FLM Vision group at NASA Ames has been developing computational models of visual processing and using them to develop computational metrics for similar problems. For example, display modeling systems use metrics for comparing proposed displays, halftoning optimizing methods use metrics to evaluate the difference between the halftone and the original, and image compression methods minimize the predicted visibility of compression artifacts. The visual discrimination models take as input two arbitrary images A and B and compute an estimate of the probability that a human observer will report that A is different from B. If A is an image that one desires to display and B is the actual displayed image, such an estimate can be regarded as an image quality metric reflecting how well B approximates A. There are additional complexities associated with the problem of evaluating the quality of radar and IR enhanced displays for AVID tasks. One important problem is the question of whether intruding obstacles are detectable in such displays. Although the discrimination model can handle detection situations by making B the original image A plus the intrusion, this detection model makes the inappropriate assumption that the observer knows where the intrusion will be. Effects of signal uncertainty need to be added to our models. A pilot needs to make decisions rapidly. The models need to predict not just the probability of a correct decision, but the probability of a correct decision by the time the decision needs to be made. That is, the models need to predict latency as well as accuracy. Luce and Green have generated models for auditory detection latencies. Similar models are needed for visual detection. Most image quality models are designed for static imagery. Watson has been developing a general spatial-temporal vision model to optimize video compression techniques. These models need to be adapted and calibrated for AVID applications.

Ahumada, AL↗

Shuttle Debris Impact Tool Assessment Using the Modern Design of Experiments

Computational tools have been developed to estimate thermal and mechanical reentry loads experienced by the Space Shuttle Orbiter as the result of cavities in the Thermal Protection System (TPS). Such cavities can be caused by impact from ice or insulating foam debris shed from the External Tank (ET) on liftoff. The reentry loads depend on cavity geometry and certain Shuttle state variables, among other factors. Certain simplifying assumptions have been made in the tool development about the cavity geometry variables. For example, the cavities are all modeled as shoeboxes , with rectangular cross-sections and planar walls. So an actual cavity is typically approximated with an idealized cavity described in terms of its length, width, and depth, as well as its entry angle, exit angle, and side angles (assumed to be the same for both sides). As part of a comprehensive assessment of the uncertainty in reentry loads estimated by the debris impact assessment tools, an effort has been initiated to quantify the component of the uncertainty that is due to imperfect geometry specifications for the debris impact cavities. The approach is to compute predicted loads for a set of geometry factor combinations sufficient to develop polynomial approximations to the complex, nonparametric underlying computational models. Such polynomial models are continuous and feature estimable, continuous derivatives, conditions that facilitate the propagation of independent variable errors. As an additional benefit, once the polynomial models have been developed, they require fewer computational resources to execute than the underlying finite element and computational fluid dynamics codes, and can generate reentry loads estimates in significantly less time. This provides a practical screening capability, in which a large number of debris impact cavities can be quickly classified either as harmless, or subject to additional analysis with the more comprehensive underlying computational tools. The polynomial models also provide useful insights into the sensitivity of reentry loads to various cavity geometry variables, and reveal complex interactions among those variables that indicate how the sensitivity of one variable depends on the level of one or more other variables. For example, the effect of cavity length on certain reentry loads depends on the depth of the cavity. Such interactions are clearly displayed in the polynomial response models.

DeLoach, R.↗

National Wind Tunnel Complex (NWTC)

The National Wind Tunnel Complex (NWTC) Final Report summarizes the work carried out by a unique Government/Industry partnership during the period of June 1994 through May 1996. The objective of this partnership was to plan, design, build and activate 'world class' wind tunnel facilities for the development of future-generation commercial and military aircraft. The basis of this effort was a set of performance goals defined by the National Facilities Study (NFS) Task Group on Aeronautical Research and Development Facilities which established two critical measures of improved wind tunnel performance; namely, higher Reynolds number capability and greater productivity. Initial activities focused upon two high-performance tunnels (low-speed and transonic). This effort was later descoped to a single multipurpose tunnel. Beginning in June 1994, the NWTC Project Office defined specific performance requirements, planned site evaluation activities, performed a series of technical/cost trade studies, and completed preliminary engineering to support a proposed conceptual design. Due to budget uncertainties within the Federal government, the NWTC project office was directed to conduct an orderly closure following the Systems Design Review in March 1996. This report provides a top-level status of the project at that time. Additional details of all work performed have been archived and are available for future reference.

Source record↗

Overview of the SAE G-11 RMSL (Reliability, Maintainability, Supportability, and Logistics) Division Activities and Technical Projects

The SAE G-11 RMSL (Reliability, Maintainability, Supportability, and Logistics) Division activities include identification and fulfillment of joint industry, government, and academia needs for development and implementation of RMSL technologies. Four Projects in the Probabilistic Methods area and two in the area of RMSL have been identified. These are: (1) Evaluation of Probabilistic Technology - progress has been made toward the selection of probabilistic application cases. Future effort will focus on assessment of multiple probabilistic softwares in solving selected engineering problems using probabilistic methods. Relevance to Industry & Government - Case studies of typical problems encountering uncertainties, results of solutions to these problems run by different codes, and recommendations on which code is applicable for what problems; (2) Probabilistic Input Preparation - progress has been made in identifying problem cases such as those with no data, little data and sufficient data. Future effort will focus on developing guidelines for preparing input for probabilistic analysis, especially with no or little data. Relevance to Industry & Government - Too often, we get bogged down thinking we need a lot of data before we can quantify uncertainties. Not True. There are ways to do credible probabilistic analysis with little data; (3) Probabilistic Reliability - probabilistic reliability literature search has been completed along with what differentiates it from statistical reliability. Work on computation of reliability based on quantification of uncertainties in primitive variables is in progress. Relevance to Industry & Government - Correct reliability computations both at the component and system level are needed so one can design an item based on its expected usage and life span; (4) Real World Applications of Probabilistic Methods (PM) - A draft of volume 1 comprising aerospace applications has been released. Volume 2, a compilation of real world applications of probabilistic methods with essential information demonstrating application type and timehost savings by the use of probabilistic methods for generic applications is in progress. Relevance to Industry & Government - Too often, we say, 'The Proof is in the Pudding'. With help from many contributors, we hope to produce such a document. Problem is - not too many people are coming forward due to proprietary nature. So, we are asking to document only minimum information including problem description, what method used, did it result in any savings, and how much?; (5) Software Reliability - software reliability concept, program, implementation, guidelines, and standards are being documented. Relevance to Industry & Government - software reliability is a complex issue that must be understood & addressed in all facets of business in industry, government, and other institutions. We address issues, concepts, ways to implement solutions, and guidelines for maximizing software reliability; (6) Maintainability Standards - maintainability/serviceability industry standard/guidelines and industry best practices and methodologies used in performing maintainability/ serviceability tasks are being documented. Relevance to Industry & Government - Any industry or government process, project, and/or tool must be maintained and serviced to realize the life and performance it was designed for. We address issues and develop guidelines for optimum performance & life.

Singhal, Surendra N.↗

PACE Technical Report Series, Volume 4: Cloud Retrievals in the PACE Mission: PACE Science Team Consensus Document

Earth is a complex dynamical system exhibiting continuous change in its atmosphere, ocean,and surface elements. Nearly all (99.97%) of the energy driving these systems is linked to the Sun. Measurements of reflected sunlight contain a unique signature of wavelength-specific scattering and absorption interactions occurring between incoming solar energy and atmospheric (molecules, aerosols,clouds) and surface features Clouds can affect significantly both shortwave and long wave radiation, depending on altitude/vertical structure, thermodynamic phase, and optical properties. Low, warm, and optically thick clouds predominantly have a cooling effect, while high, cold, optically thin clouds can cause warming by absorbing warmer radiation emitted from the surface and lower atmosphere.When the net difference between outgoing and incoming solar radiation is matched by the net infrared radiation emitted to space, the Earth's climate is in radiative balance. While radiative forcing components (GHGs, aerosols - direct and indirect) contribute to a net radiative imbalance, climate sensitivity is ultimately determined by the contribution of various system feed backs. The role of cloud feedback in a warming climate is currently the largest inter-model uncertainty in climate sensitivity and therefore in climate prediction [Bony and Dufresne 2005]. A comprehensive understanding of current cloud propertiesand dynamic/microphysical processes requires a global perspective from satellites.

Plankton, Aerosol, Cloud, ocean Ecosystem (PACE)↗

Advances in Measuring the Apparent Optical Properties (AOPs) of Optically Complex Waters

This report documents new technology used to measure the apparent optical properties (AOPs) of optically complex waters. The principal objective is to be prepared for the launch of next-generation ocean color satellites with the most capable commercial off-the-shelf (COTS) instrumentation. An enhanced COTS radiometer was the starting point for designing and testing the new sensors. The follow-on steps were to apply the lessons learned towards a new in-water profiler based on a kite-shaped backplane for mounting the light sensors. The next level of sophistication involved evaluating new radiometers emerging from a development activity based on so-called microradiometers. The exploitation of microradiometers resulted in an in-water profiling system, which includes a sensor networking capability to control ancillary sensors like a shadowband or global positioning system (GPS) device. A principal advantage of microradiometers is their flexibility in producing, interconnecting, and maintaining instruments. The full problem set for collecting sea-truth data--whether in coastal waters or the open ocean-- involves other aspects of data collection that were improved for instruments measuring both AOPs and inherent optical properties (IOPs), if the uncertainty budget is to be minimized. New capabilities associated with deploying solar references were developed as well as a compact solution for recovering in-water instrument systems from small boats.

Morrow, John H.↗