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NASA NTRSDate not supplied

Using the System Complexity Metric (SCM) to Compare CO2 Removal Systems

A fundamental cause of difficulty in large engineering projects is their inherent complexity. An impression of complexity occurs if a system is simply difficult to understand, where there is no obvious mental model that correctly predicts its behavior. Higher system complexity is usually associated with higher cost and higher failure rate. Complexity is perceived if a system has many diverse components, multiple interactions and feedback loops, transients and dynamic behavior, and unanticipated failure modes. Identifying and removing these signs of complexity should improve performance and reduce the cost and failure rate. Complexity can be directly measured by the number of components and their interactions. The System Complexity Metric (SCM) is defined as the sum of the number of parts in a system, N, plus the number of the one-way interconnections between them, I. SCM = N + I. The SCM is easily determined by direct inspection of the system block diagram. SCM can be used to compare systems and to guide their redesign to reduce cost and failure rate. Carbon dioxide removal systems are analyzed using SCM, cost, and failure rate. As in previous work, cost is directly proportional to SCM and that failure rate increases as a power of SCM for large differences in SCM. The SCM ranking of carbon dioxide removal systems is the same as their ranking in detailed analysis and practice.

Harry W. Jones↗
NASA NTRSDate not supplied

Using the System Complexity Metric (SCM) to Compare CO2 Reduction Systems

A fundamental cause of difficulty in large engineering projects is their inherent complexity. An impression of complexity occurs if a system is simply difficult to understand, where there is no obvious mental model that correctly predicts its behavior. Higher system complexity is usually associated with higher cost and higher failure rate. Complexity is perceived if a system has many diverse components, multiple interactions and feedback loops, transients and dynamic behavior, and unanticipated failure modes. Identifying and removing these signs of complexity should improve performance and reduce the cost and failure rate. Complexity can be directly measured by the number of components and their interactions. The System Complexity Metric (SCM) is defined as the sum of the number of parts in a system, N, plus the number of the one-way interconnections between them, I. SCM = N + I. The SCM is easily determined by direct inspection of the system block diagram. SCM can be used to compare systems and to guide their redesign to reduce cost and failure rate. Carbon dioxide reduction systems are analyzed using SCM, cost, and failure rate. As in previous work, cost is directly proportional to SCM and that failure rate increases as a power of SCM for large differences in SCM. The SCM ranking of carbon dioxide reduction systems is the same as their ranking in detailed analysis and practice.

Harry W. Jones↗
NASA NTRSDate not supplied

The System Complexity Metric (SCM) Explains Systems Design and is Correlated with Cost and Failure Rate

The human short term memory span and working capacity is limited to three to five items, especially if they are organized complex “chunks” of information. The impression of complexity occurs when a system is simply difficult to understand, where there is no apparent pattern to predict its behavior. Hierarchical systems design can reduce perceived complexity and increase the amount of information that can be managed. The SCM was developed to measure complexity and help compare proposed overall system architectures before detailed design information is available. The SCM is defined as the sum of the number of major nodes, N, in the system block diagram plus the number of one-way interactions, I, between the nodes. SCM = N + I. SCM’s are easily determined by direct inspection of high-level block diagrams of life support systems. Axiomatic design develops a hierarchy of subsystem requirements and designs together in a top-down, back-and-forth process. A coupling matrix is used to control the relationships between the subsystem functions and design concepts. Axiomatic design can improve system design by decoupling requirements and designs. Axiomatic design was applied to the planning of a closed life support system, similar to that used on the International Space Station. A materially open as opposed to a closed system design was created by removing the interconnections required to close the system. The open system had the same number of designed subsystems as the closed system, but it had many fewer interconnections and its SCM was lower by about half. The costs were estimated and the MTBF (Mean Time Before Failure) tabulated for open and closed space life support systems. The estimated costs were linearly proportional to SCM for the wide variations of SCM in life support, but small differences may not be significant. The flight and preflight MTBF’s both declined exponentially with increasing MTBF, faster than MTBF-2, even though the preflight estimated MTBF’s were about ten times higher than the flight MTBF’s.

System Complexity Metric (SCM)↗
NASA NTRSDate not supplied

Applying the System Complexity Metric (SCM)

A fundamental cause of difficulty in larger engineering projects is their inherent complexity. An impression of complexity occurs if a system is simply difficult to understand, so that there is no obvious mental model that correctly predicts its behavior. Higher complexity is usually associated with higher cost and higher failure rate. Complexity is indicated by a system having more and diverse components, multiple interactions and feedback loops, transients and dynamic behavior, and often the emergence of unanticipated failure modes. Identifying and removing these signs of complexity should reduce complexity and improve performance. Here we limit complexity measurement to the number of components and their interactions. A System Complexity Metric (SCM) is defined as equal to the sum of the number of parts in a system, N, plus the sum of the one-way interconnections between them, I. SCM = N + I. The SCM is easily determined by direct inspection of system block diagrams. Previous work found that life support system cost was directly proportional to SCM and that failure rate increased faster than SCM squared. SCM can be used to compare systems or to guide their redesign to reduce cost and failure rate. Carbon dioxide removal systems will be analyzed using SCM, cost, and failure rate.

Harry W Jones↗
NASA NTRSDate not supplied

The System Complexity Metric (SCM) Predicts System Costs and Failure Rates

A complex system has many parts and interactions and so is difficult to understand. Systems with higher complexity generally have higher costs and failure rates. A System Complexity Metric (SCM) is defined to be the sum of the number of nodes, N, in the system block diagram plus the number of one-way interactions, I, between the nodes. SCM = N + I. SCMs are easily determined by direct inspection of high level block diagrams of life support systems. System cost was found to be directly proportional to SCM. The system MTBF (Mean Time Before Failure) is the inverse of the system failure rate. MTBF = 1/f. The system MTBF was found to be proportional to SCM^(-2.2) for estimated preflight MTBFs. As is typical for systems that are not extensively tested and redesigned to eliminate unexpected failure modes, the life support flight failure rates were about ten times higher than the preflight estimates and the MTBFs one-tenth the preflight estimates. The system MTBF was found to be proportional to SCM^(-2.6) for observed flight MTBFs.

System compleity↗
NASA NTRS1980

Application handbook for a Standardized Control Module (SCM) for DC-DC converters, volume 1

The standardized control module (SCM) was developed for application in the buck, boost and buck/boost DC-DC converters. The SCM used multiple feedback loops to provide improved input line and output load regulation, stable feedback control system, good dynamic transient response and adaptive compensation of the control loop for changes in open loop gain and output filter time constraints. The necessary modeling and analysis tools to aid the design engineer in the application of the SCM to DC-DC Converters were developed. The SCM functional block diagram and the different analysis techniques were examined. The average time domain analysis technique was chosen as the basic analytical tool. The power stage transfer functions were developed for the buck, boost and buck/boost converters. The analog signal and digital signal processor transfer functions were developed for the three DC-DC Converter types using the constant on time, constant off time and constant frequency control laws.

Lee, F. C.↗
NASA NTRS1980

User's design handbook for a Standardized Control Module (SCM) for DC to DC Converters, volume 2

A unified design procedure is presented for selecting the key SCM control parameters for an arbitrarily given power stage configuration and parameter values, such that all regulator performance specifications can be met and optimized concurrently in a single design attempt. All key results and performance indices, for buck, boost, and buck/boost switching regulators which are relevant to SCM design considerations are included to facilitate frequent references.

Lee, F. C.↗
NASA NTRS1984

SCM Handbooks for dc-to-dc Converters

Two documents aid in design of control modules for dc-to-dc converters. Features of SCM include: Adaptive stability, power component stress limiting, implementation of various control laws, unified design approach. Analysis and quidelines contained in handbooks enable engineer to design SCM circuit and confidently predict resulting overall performance.

Lee, F.↗
NASA NTRS2004

Influence of Sub-grid-Scale Isentropic Transports on McRAS Evaluations using ARM-CART SCM Datasets

In GCM-physics evaluations with the currently available ARM-CART SCM datasets, McRAS produced very similar character of near surface errors of simulated temperature and humidity containing typically warm and moist biases near the surface and cold and dry biases aloft. We argued it must have a common cause presumably rooted in the model physics. Lack of vertical adjustment of horizontal transport was thought to be a plausible source. Clearly, debarring such a freedom would force the incoming air to diffuse into the grid-cell which would naturally bias the surface air to become warm and moist while the upper air becomes cold and dry, a characteristic feature of McRAS biases. Since, the errors were significantly larger in the two winter cases that contain potentially more intense episodes of cold and warm advective transports, it further reaffirmed our argument and provided additional motivation to introduce the corrections. When the horizontal advective transports were suitably modified to allow rising and/or sinking following isentropic pathways of subgrid scale motions, the outcome was to cool and dry (or warm and moisten) the lower (or upper) levels. Ever, crude approximations invoking such a correction reduced the temperature and humidity biases considerably. The tests were performed on all the available ARM-CART SCM cases with consistent outcome. With the isentropic corrections implemented through two different numerical approximations, virtually similar benefits were derived further confirming the robustness of our inferences. These results suggest the need for insentropic advective transport adjustment in a GCM due to subgrid scale motions.

Sud, Y. C.↗
NASA NTRS2005

Cloud Properties Simulated by a Single-Column Model. Part II: Evaluation of Cumulus Detrainment and Ice-phase Microphysics Using a Cloud Resolving Model

This paper is the second in a series in which kilometer-scale-resolving observations from the Atmospheric Radiation Measurement program and a cloud-resolving model (CRM) are used to evaluate the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model. Part I demonstrated that kilometer-scale cirrus properties simulated by the SCM significantly differ from the cloud radar observations while the CRM simulation reproduced most of the cirrus properties as revealed by the observations. The present study describes an evaluation, through a comparison with the CRM, of the SCM's representation of detrainment from deep cumulus and ice-phase microphysics in an effort to better understand the findings of Part I. It is found that detrainment occurs too infrequently at a single level at a time in the SCM, although the detrainment rate averaged over the entire simulation period is somewhat comparable to that of the CRM simulation. Relatively too much detrained ice is sublimated when first detrained. Snow falls over too deep of a layer due to the assumption that snow source and sink terms exactly balance within one time step in the SCM. These characteristics in the SCM parameterizations may explain many of the differences in the cirrus properties between the SCM and the observations (or between the SCM and the CRM). A possible improvement for the SCM consists of the inclusion of multiple cumulus cloud types as in the original Arakawa-Schubert scheme, prognostically determining the stratiform cloud fraction and snow mixing ratio. This would allow better representation of the detrainment from deep convection, better coupling of the volume of detrained air with cloud fraction, and better representation of snow field.

Luo, Yali↗
NASA NTRS2023

Analysis of Strategic Conflict Management Approaches as Applied to Simulated UAM Operations

This report presents the results of a comparison analysis of candidate Strategic Conflict Management (SCM) strategies as applied to Urban Air Mobility (UAM) operations. The SCM strategies investigated included: no SCM, resource scheduling (RS), resource flow rates (FR), area-based flow rates (AR), and conflict detection and resolution (CR). The study evaluated each strategy against the same 3 levels of flight demand in a representative airspace construct for the Dallas/Fort Worth region. The study also accounted for different levels of uncertainty in operational planning and equivalent levels of trajectory following error. In the analysis, we compared the SCM strategies’ effectiveness in reducing the need for the tactical conflict management layer to act and looked at the metrics of unmitigated losses-of-separation (LOS), flight delays imposed by strategic planning, and throughput of the overall airspace. The study results indicated that the CR strategy was the most effective at reducing LOS and percentage of flights with LOS, even in the presence of trajectory error when uncertainty is accounted for in planning. Thus, if the objective is to reduce the number of actions that the tactical conflict management layer will have to take, in terms of conflicts that may need to be resolved, CR is the strategy to use. The FR strategy was found to be the worst at reducing LOS and percentage of flights with LOS. Thus, it is not very effective at reducing the actions required by a tactical conflict management layer. In the airspace tested, the demand was high enough to produce unacceptable levels of flight delay and reductions of throughput when the SCM strategies were implemented. This was especially evident at the higher levels of trajectory uncertainty and error. The need to account for expected levels of uncertainty becomes more and more important as the demand level increases and as the level of trajectory error increases. This is because the likelihood of flights with LOS increases as the density of operations increases and as the level of trajectory error increases. Accounting for uncertainty in the SCM strategies improves the strategy effectiveness with respect to LOS but increases delays and reduces throughput. Thus, there is a tradeoff between scalability and allowable levels of uncertainty. That is, we can implement an air traffic management construct that allows high levels of uncertainty, but we can expect that same system to have limits on scalability that may be evident even at small demand levels, such as those used in this study. Therefore, the results in this study indicate that an air traffic system should attempt to implement mechanisms appropriate for reducing uncertainty where possible in order to increase the chances for scalability. And this increased level of predictability of operations needs to be balanced with mechanisms for ensuring flexibility when operational conditions and plans need to change, even though those types of changes should be the exception rather than the rule under normal conditions. The study also introduced a trade space that could serve as a mechanism for selecting the appropriate SCM strategy in a trade-off between uncertainty and error, mean flight delay, and the LOS metrics (which this study equates to the potential for tactical conflict management actions). The optimal solution for a given airspace, demand level, and other factors, could likely be a combination of SCM strategies, although this study only compared the use of a single SCM strategy at a time. The CR strategy appeared to have the best opportunity for scalability by limiting the number of potential tactical actions to nearly zero.

Strategic Conflict Management↗
NASA NTRS2012

The Single Crew Module Concept for Exploration

Many concepts have been proposed for exploring space. In early 2010 presidential direction called for reconsidering the approach to address changes in exploration destinations, use of new technologies and development of new capabilities to support exploration of space. Considering the proposed new technology and capabilities that NASA was directed to pursue, the single crew module (SCM) concept for a more streamlined approach to the infrastructure and conduct of exploration missions was developed. The SCM concept combines many of the new promising technologies with a central concept of mission architectures that uses a single habitat module for all phases of an exploration mission. Integrating mission elements near Earth and fully fueling them prior to departure of the vicinity of Earth provides the capability of using the single habitat both in transit to an exploration destination and while exploring the destination. The concept employs the capability to return the habitat and interplanetary propulsion system to Earth vicinity so that those elements can be reused on subsequent exploration missions. This paper describes the SCM concept, provides a top level mass estimate for the elements needed and trades the concept against Many concepts have been proposed for exploring space. In early 2010 presidential direction called for reconsidering the approach to address changes in exploration destinations, use of new technologies and development of new capabilities to support exploration of space. Considering the proposed new technology and capabilities that NASA was directed to pursue, the single crew module (SCM) concept for a more streamlined approach to the infrastructure and conduct of exploration missions was developed. The SCM concept combines many of the new promising technologies with a central concept of mission architectures that uses a single habitat module for all phases of an exploration mission. Integrating mission elements near Earth and fully fueling them prior to departure of the vicinity of Earth provides the capability of using the single habitat both in transit to an exploration destination and while exploring the destination. The concept employs the capability to return the habitat and interplanetary propulsion system to Earth vicinity so that those elements can be reused on subsequent exploration missions. This paper describes the SCM concept, provides a top level mass estimate for the elements needed and trades the concept against Constellation approaches for Lunar, Near Earth Asteroid and Mars Surface missions.

Chambliss, Joe↗
NASA NTRS1990

System control module diagnostic Expert Assistant

The Orbiter EXperiments (OEX) Program was established by NASA's Office of Aeronautics and Space Technology (OAST) to accomplish the precise data collection necessary to support a complete and accurate assessment of Space Transportation System (STS) Orbiter performance during all phases of a mission. During a mission, data generated by the various experiments are conveyed to the OEX System Control Module (SCM) which arranges for and monitors storage of the data on the OEX tape recorder. The SCM Diagnostic Expert Assistant (DEA) is an expert system which provides on demand advice to technicians performing repairs of a malfunctioning SCM. The DEA is a self-contained, data-driven knowledge-based system written in the 'C' Language Production System (CLIPS) for a portable micro-computer of the IBM PC/XT class. The DEA reasons about SCM hardware faults at multiple levels; the most detailed layer of encoded knowledge of the SCM is a representation of individual components and layouts of the custom-designed component boards.

Flores, Luis M.↗
NASA NTRS1999

Configuration Management of an Optimization Application in a Research Environment

Multidisciplinary design optimization (MDO) research aims to increase interdisciplinary communication and reduce design cycle time by combining system analyses (simulations) with design space search and decision making. The High Performance Computing and Communication Program's current High Speed Civil Transport application, HSCT4.0, at NASA Langley Research Center involves a highly complex analysis process with high-fidelity analyses that are more realistic than previous efforts at the Center. The multidisciplinary processes have been integrated to form a distributed application by using the Java language and Common Object Request Broker Architecture (CORBA) software techniques. HSCT4.0 is a research project in which both the application problem and the implementation strategy have evolved as the MDO and integration issues became better understood. Whereas earlier versions of the application and integrated system were developed with a simple, manual software configuration management (SCM) process, it was evident that this larger project required a more formal SCM procedure. This report briefly describes the HSCT4.0 analysis and its CORBA implementation and then discusses some SCM concepts and their application to this project. In anticipation that SCM will prove beneficial for other large research projects, the report concludes with some lessons learned in overcoming SCM implementation problems for HSCT4.0.

Townsend, James C.↗
NASA NTRS2000

Influence of the Biosphere on Precipitation: July 1995 Studies with the ARM-CART Data

Ensemble sets of simulation experiments were conducted with a single column model (SCM) using the Goddard GEOS II GCM physics containing a recent version of the Cumulus Scheme (McRAS) and a biosphere based land-fluxes scheme (SSiB). The study used the 18 July to 5 August 1995 ARM-CART (Atmospheric Radiation Measurement-Cloud Atmospheric Radiation Test-bed) data, which was collected at the ARM-CART site in the mid-western United States and analyzed for single column modeling (SCM) studies. The new findings affirm the earlier findings that the vegetation, which increases the solar energy absorption at the surface together with soil and soil-moisture dependent processes, which modulate the surface, fluxes (particularly evapotranspiration) together help to increase the local rainfall. In addition, the results also show that for the particular study period roughly 50% of the increased evaporation over the ARM-CART site would be converted into rainfall with the Column, while the remainder would be advected out to the large-scale. Notwithstanding the limitations of only one-way interaction (i.e., the large-scale influencing the regional physics and not vice versa), the current SCM simulations show a very robust relationship. The evaporation-precipitation relationship turns out to be independent of the soil types, and soil moisture; however, it is weakly dependent on the vegetation cover because of its surface-albedo effect. Clearly, these inferences are prone to weaknesses of the SCM physics, the assumptions of the large-scale being unaffected by gridscale (SCM-scale) changes in moist processes, and other limitations of the evaluation procedures.

Sud, Y. C.↗
NASA NTRS2004

A Novel Spacecraft Charge Monitor for LEO

Five years ago we introduced a new method for measuring spacecraft chassis floating potential relative to the space plasma (absolute spacecraft potential) in low Earth orbit. The method, based on a straightforward interpretation of photoelectron spectra, shows promise for numerous applications, but has not yet been tried. In the interest of testing the method, and ultimately supplying another tool for measuring absolute spacecraft charge, we are producing a flight prototype Spacecraft Charge Monitor (SCM) with support from NASA's Small Business Innovation Research (SBIR) program. Although insight into the technique came from data collected in space over two decades ago, very little data are available. The data indicate that it may be possible to determine spacecraft floating potential to within 0.1 volt each with the SCM second under certain conditions. It is debatable that spacecraft floating potential has ever been measured with such accuracy. The compact, easily deployed SCM also offers the advantage of long-term stability in calibration. Accurate floating potential determinations from the SCM could be used to correct biases in space plasma measurements and evaluate charge mitigation and/or sensing devices. Although this paper focuses on the device's use in low Earth orbit (LEO), the device may also be able to measure spacecraft charge at higher altitudes, in the solar wind, and in orbits around other planets. The flight prototype SCM we are producing for delivery to NASA in the third quarter of 2004 will measure floating potential from 0 to -150 volts with 0.1 volt precision, weigh approximately 600-700 grams, consume approximately 2 watts, and will measure approximately 8 x 10 x 17 cm.

Goembel, Luke↗