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DOE OSTI2023

Uncertain Spatial Pattern of Future Land Use and Land Cover Change and Its Impacts on Terrestrial Carbon Cycle Over the Arctic–Boreal Region of North America

Land use and land cover change (LULCC) represents a key process of human-Earth system interaction and has profound impacts on terrestrial ecosystem carbon cycling. As a key input for ecosystem models, future gridded LULCC data is typically spatially downscaled from regional LULCC projections by integrated assessment models, such as the Global Change Analysis Model (GCAM). The uncertainty associated with the different spatial downscaling methods and its impacts on the subsequent model projections have been historically ignored and rarely examined. This study investigated this problem using two representative spatial downscaling methods and focused on their impacts on the carbon cycle over the Arctic-Boreal Vulnerability Experiment (ABoVE) domain, where extensive LULCC is expected. Specifically, we used the Future Land Use Simulation model (FLUS) and the Demeter model to generate 0.25° gridded LULCC data (i.e., LULCC FLUS and LULCC Demeter , respectively) with the same input of regional LULCC projections from GCAM, under both the low (i.e., SSP126) and high (i.e., SSP585) greenhouse gas emission scenarios. The two sets of downscaled LULCC were used to drive the Community Land Model version 5 and prognostically simulate the terrestrial carbon cycle dynamics over the 21st century. The results suggest large spatial-temporal differences between LULCC FLUS and LULCC Demeter , and the spatial distributions of the needleleaf evergreen boreal tree, broadleaf deciduous boreal tree, broadleaf deciduous boreal shrub, and C3 arctic grass are particularly different under both SSP126 and SSP585. Additionally, the spatiotemporal differences are larger under SSP126 than SSP585, due to more intensive LULCC under SSP126 than SSP585 from GCAM projection. The differences in LULCC further lead to large discrepancies in the spatial patterns of projected gross primary productivity, ecosystem respiration, and net ecosystem exchange, which represent more than 79% of the contributions of future LULCC in 2100. Additionally, the difference in carbon flux under SSP126 is generally larger than those under SSP585. This study highlights the importance of considering the uncertainties induced by the spatial downscaling process in future LULCC projections and carbon cycle simulations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Hysteretic temperature sensitivity of wetland CH4 fluxes explained by substrate availability and microbial activity: Model Archive

This Modeling Archive is in support of an NGEE Arctic publication "Hysteretic temperature sensitivity of wetland CH4 fluxes explained by substrate availability and microbial activity" in the Journal Biogeosciences (https://doi.org/10.5194/bg-17-5849-2020), which includes the model data used in the publication. CH4 emissions from terrestrial systems are posited to increase, which can offset mitigation efforts and accelerate climate change. Yet, the accuracy of modeled CH4 emissions is sensitive to the prescribed CH4 production (or emission) temperature dependencies that are currently uncertain. Here, we use a comprehensive biogeochemistry model (ecosys) to investigate factors modulating CH4 production and emission rates across a permafrost thaw gradient encompassing a partly thawed bog and a fully thawed fen. We find that seasonally varying substrate availability drives lower and higher modeled methanogen biomass and activity, and thereby CH4 production, during the earlier and later periods of the thawed season, respectively. Package follows the Model data archiving guidelines with data in a *.zip file with three subfolders containing *.csv files and raw model output files; a data dictionary table (data_dictionary.csv) and two model output description tables (ecosys_plantspecies_output_notes.csv and ecosys_soil_ouput_notes.csv) to explain the format and meaning of individual output variables; and a user guide as a *.pdf. A detailed model description can be found in the supplement of (Grant, 2013). The ecosys source code is available at https://doi:10.5281/zenodo.3906642. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2018

Link Between Arctic Tropospheric BrO Explosion Observed from Space and Sea-Salt Aerosols from Blowing Snow Investigated Using Ozone Monitoring Instrument BrO Data and GEOS-5 Data Assimilation System

Bromine radicals (Br + BrO) are important atmospheric species owing to their ability to catalytically destroy ozone as well as their potential impacts on the oxidative pathways of many trace gases, including dimethylsulfide and mercury. Using space-based observations of BrO, recent studies have reported rapid enhancements of tropospheric BrO over large areas (so called "BrO explosions") connected to near-surface ozone depletion occurring in polar spring. However, the source(s) of reactive bromine and mechanism(s) that initiate these BrO explosions are uncertain. In this study, we investigate the relationships between Arctic BrO explosions and two of the proposed sources of reactive bromine: sea-salt aerosol (SSA) generated from blowing snow and first-year (seasonal) sea ice. We use tropospheric column BrO derived from the Ozone Monitoring Instrument (OMI) in conjunction with the Goddard Earth Observing System Version 5 (GEOS-5) data assimilation system provided by National Aeronautics and Space Administration Global Modeling and Assimilation Office. Case studies demonstrate a strong association between the temporal and spatial extent of OMI-observed BrO explosions and the GEOS-5 simulated blowing snow-generated SSA during Arctic spring. Furthermore, the frequency of BrO explosion events observed over the 11-year record of OMI exhibits significant correlation with a time series of the simulated SSA emission flux in the Arctic and little to no correlation with a time series of satellite-based first-year sea ice area. Therefore, we conclude that SSA generated by blowing snow is an important factor in the formation of the BrO explosion observed from space during Arctic spring.

blowing snow↗

NASA NTRS2015

Modelling Groundwater Depletion at Regional and Global Scales: Present State and Future Prospects.

Except for frozen water in ice and glaciers, groundwater is the world's largest distributed store of freshwater and has strategic importance to global food and water security. In this paper, the most recent advances quantifying groundwater depletion (GWD) are comprehensively reviewed. This paper critically evaluates the recently advanced modeling approaches estimating GWD at regional and global scales, and the evidence of feedbacks to the Earth system including sea-level rise associated with GWD. Finally, critical challenges and opportunities in the use of groundwater are identified for the adaption to growing food demand and uncertain climate.

Groundwater Depletion (GWD)↗

DOE OSTI2022

Tri-level hybrid interval-stochastic optimal scheduling for flexible residential loads under GAN-assisted multiple uncertainties

Various building loads, such as heating, ventilation, and air conditioners (HVACs), electric water heaters (EWHs), and electric vehicles (EVs), can introduce opportunities for improving the flexibility of electricity consumption while satisfying the needs of building owners as well as benefiting the resilience of distribution system. To utilize such flexibility, a tri-level distribution market framework is established, including residential consumers, load aggregators (LAs), and the distribution system operator (DSO). In this work, the uncertainties from all three levels are considered. The random consumption behavior at the consumer level is modeled as a Gaussian noise that is also aggregated and transmitted to the LA level. The weather temperature in the LA level is forecasted as an interval, and the photovoltaic (PV) power in the market-clearing level is modeled by a set of power scenarios generated by Generative Adversarial Networks (GANs). Then, a hybrid interval-stochastic programming is proposed to transform the uncertain problems in the first two levels into deterministic ones. For real-time implementations, a rolling horizon optimization (RHO) scheme is employed to continuously optimize the power consumption based on the latest operating information. Finally, case studies on a modified IEEE 69-bus system validate the effectiveness of the proposed uncertainty modeling strategies and the RHO scheme.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1981

The in-flight performance of the Solar Maximum Mission Electrical Power System

Circuitry, power handling, and operational characteristics and anomalies of the Electrical Power System (EPS) of the Solar Maximum Mission are discussed. The EPS is designed as a standard unit to be a candidate for use on future space missions. Blown, improperly derated fuses in the Attitude Control System and the Signal Conditioning Assembly have led to switching to magnetrons for solar angle, with a loss of accuracy, and a loss of one-half of telemetry data, respectively. In addition, reasons for an 11-14% degradation of solar array output are uncertain due to the loss of precise attitude control. Current surges to peak at 76.5 A (down from 94.5 A) at sunrise, stays for four to five minutes, then resumes nominal output for the remainder of the 61-68 daytime period. Eclipse varies between 28 and 35 minutes, with corresponding depth of discharge of 14%. The batteries charge at 20 A, and although an overcharge mode has been continuously sensed, operation has been normal and temperature sensors have not indicated overcharge; cell failure has also not been sensed. The system has a two year design life and a desired life of four years.

Broderick, R. J.↗

DOE OSTI2023

A hybrid data-driven and model-based approach for computationally efficient stochastic unit commitment and economic dispatch under wind and solar uncertainty

Stochastic unit commitment (UC) and economic dispatch (ED) are imperative in dealing with uncertainty in renewable forecast for power system operation and planning such that the overall expected production cost is minimized over the planning horizon. However, accurate calculation of the expected production cost requires assessment of a very large number of different scenarios of uncertain renewable resources, such as solar and wind, which is practically infeasible to simulate in real time. This article proposes a hybrid datadriven and physics-based model-predictive paradigm to efficiently solve for stochastic unit commitment and economic dispatch considering uncertainty in wind and solar power forecasts. Here, the novelty of the approach lies in decoupling the production cost estimation from the unit commitment and economic dispatch optimization problems under uncertainty without compromising on the fidelity of the solutions. A data-driven machine learning model is first developed to predict the mean optimal production cost. A physics-based inverse problem is then solved to get the stochastic UC and ED profiles from the expected cost. The presented approach considers, for the first time, solar uncertainty in UC/ED determination and enables efficient and accurate propagation of wind and solar uncertainty to estimate the statistics of the production cost. The effectiveness of the developed approach is demonstrated systematically on a stylized RTS-GMLC single-node system. The overall framework predicts the expected cost 62.5% more accurately than the existing state-of-the-art, on unforeseen days during the entire year, and yields, for the first time, the associated physically consistent UC and ED profiles. The solutions are also shown to be flexible in providing adequate daily reserves to address any statistical deviations from probabilistic power forecasts. The computational time associated with the presented method is only about 10 s compared to over 24 h needed for a conventional stochastic UC/ED determination under uncertainty on an Intel Core i9 processor with 32 GB of RAM.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Nucleosynthesis of an 11.8 M ⊙ Supernova with 3D Simulation of the Inner Ejecta: Overall Yields and Implications for Short-lived Radionuclides in the Early Solar System

Based on a 3D supernova simulation of an 11.8 M ⊙ progenitor model with an initial solar composition, we study the nucleosynthesis using tracers covering the innermost 0.1 M ⊙ of the ejecta. These ejecta are mostly proton-rich and contribute significant amounts of 45 Sc and 64 Zn. The production of heavier isotopes is sensitive to the electron fraction and hence the neutrino emission from the proto-neutron star. The yields of these isotopes are rather uncertain due to the approximate neutrino transport used in the simulation. In order to obtain the total yields for the whole supernova, we combine the results from the tracers with those for the outer layers from a suitable 1D model. Using the yields of short-lived radionuclides (SLRs), we explore the possibility that an 11.8 M ⊙ supernova might have triggered the formation of the solar system and provided some of the SLRs measured in meteorites. In particular, we discuss two new scenarios that can account for at least the data on 41 Ca, 53 Mn, and 60 Fe without exceeding those on the other SLRs.

Astronomy & Astrophysics↗

DOE OSTI2020

Efficient proactive vehicle relocation for on-demand mobility service with recurrent neural networks

One major challenge for on-demand mobility service (OMS) providers is to seamlessly match empty vehicles with trip requests so that the total vacant mileage is minimized. In this work, we develop an innovative data-driven approach for devising efficient vehicle relocation policy for OMS that (1) proactively relocates vehicles before the demand is observed and (2) reduces the inequality among drivers' income so that the proactive relocation policy is fair and is likely to be followed by drivers. Our approach represents the fusion of optimization and machine learning methods, which comprises three steps: First, we formulate the optimal proactive relocation as an optimal/stable matching problems and solve for global optimal solutions based on historical data. Second, the optimal solutions are then grouped and fed to train the deep learning models which consist of fully connected layers and long short-term memory networks. Low rank approximation is introduced to reduce the model complexity and improve the training performances. Finally, we use the trained model to predict the relocation policy which can be implemented in real time. We conduct comprehensive numerical experiments and sensitivity analyses to demonstrate the performances of the proposed method using New York City taxi data. Here, the results suggest that our method will reduce empty mileage per trip by 54-70% under optimal matching strategy, and a 25-32% reduction can also be achieved by following stable matching strategy. We also validate that the predicted relocation policies are robust in the presence of uncertain passenger demand level and passenger trip-requesting behavior.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

The promise of energy-efficient battery-powered urban aircraft

Improvements in rechargeable batteries are enabling several electric urban air mobility (UAM) aircraft designs with up to 300 mi of range with payload equivalents of up to seven passengers. Novel UAM aircraft consume between 130 Wh/passenger-mi and ∼ 1,200 Wh/passenger-mi depending on the design and utilization, compared to an expected consumption of over 220 Wh/passenger-mi and 1,000 Wh/passenger-mi for terrestrial electric vehicles and combustion engine vehicles, respectively. We also find that several UAM aircraft designs are approaching technological viability with current Li-ion batteries, based on the specific power and energy, while rechargeability and lifetime performance remain uncertain. These aspects highlight the technological readiness of a new segment of transportation.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Leveraging Flexible Smart Manufacturing to Accelerate Industrial Supply Chain Recovery

Any major crisis such as the latest coronavirus disease pandemic will have a monumental effect on the worldwide economy and on the international supply chain. Much of the global supply chain relies on China, Germany, and the United States for manufacturing and distribution; this fragile system is subject to failure. Climactic changes in demand and rapid shortages in necessities are the results of the pandemic’s disruption. The recovery forecast for the ongoing pandemic is uncertain and, therefore, any recovery effort will need to be adaptable to build the supply chain resiliency. A wide adoption of flexible smart automated technologies in the manufacturing sector are helping to build robust supply chains and assisting in recovery. Here, a brief discussion of these smart manufacturing technologies is presented, along with a list of potential supply chain issues and corresponding solutions. Such smart manufacturing technologies possess the potential to empower and revolutionize the traditional manufacturing environment by enhancing its resiliency and flexibility. These smart technologies will play a crucial role in accelerating the worldwide supply chain recovery in and after a pandemic.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS1987

Analytical design of intelligent machines

The problem of designing 'intelligent machines' to operate in uncertain environments with minimum supervision or interaction with a human operator is examined. The structure of an 'intelligent machine' is defined to be the structure of a Hierarchically Intelligent Control System, composed of three levels hierarchically ordered according to the principle of 'increasing precision with decreasing intelligence', namely: the organizational level, performing general information processing tasks in association with a long-term memory; the coordination level, dealing with specific information processing tasks with a short-term memory; and the control level, which performs the execution of various tasks through hardware using feedback control methods. The behavior of such a machine may be managed by controls with special considerations and its 'intelligence' is directly related to the derivation of a compatible measure that associates the intelligence of the higher levels with the concept of entropy, which is a sufficient analytic measure that unifies the treatment of all the levels of an 'intelligent machine' as the mathematical problem of finding the right sequence of internal decisions and controls for a system structured in the order of intelligence and inverse order of precision such that it minimizes its total entropy. A case study on the automatic maintenance of a nuclear plant illustrates the proposed approach.

Saridis, George N.↗

NASA NTRS1994

Robust stability of second-order systems

Nonlinear control using feedback linearization or inverse dynamics for robotic manipulators yields good results in the absence of modeling uncertainty. However, modeling uncertainties due to unknown joint friction coefficients and payload variations can give rise to undesirable characteristics when these control systems are implemented. It is shown how passivity concepts can be used to supplement the feedback linearization control design technique, in order to make it robust with respect to the uncertain effects mentioned above. Results are obtained for space manipulators with freely floating base; however, they are applicable to fixed base manipulators as well. The controller guarantees asymptotic tracking of the joint variables. Closed-loop simulation results are illustrated for planar space manipulators for cases where uncertainty exists in friction modeling and payload inertial parameters.

Chuang, C.-H.↗

NASA NTRS1994

Neptune's inner magnetosphere and aurora: Energetic particle constraints

A dramatic and peculiar dropout of greater than 500-keV ions (but not electrons) was observed within Neptune's inner magnetosphere near 2 R(sub N) as the Voyager 2 spacecraft approached the planet. Unlike a number of other energetic particle features this feature could not be accounted for by known material bodies in the context of the most utilized magnetic field models (neither the offset tilted dipole models nor the spehrical harmonic model 'O8'). However, the configuration of Neptune's inner magnetosphere is highly uncertain. By applying a novel technique, utilizing energetic particle measurements, to constrain the magnetic field configuration of the inner regions, we show that appeals to unobserved materials within Neptune's system are unnecessary, and that the ion dropout feature was, in all likelihood, the result of ion interactions with maximum L excursions of the ring 1989N1R. The constraints also favor the se of the M2 magnetic field model (Selesnick, 1992) over the previous models. An electron feature was probably absent because the electron interactions with the ring occurred substantially before the ion interactions (about 2 hours for the electrons versus a few minutes for the ions). Pitch-angle scattering apparently eliminated the electron signature. Minimum scattering rates determined based on this premise yield enough electron precipitation power to explain the brightest component of Neptune's aurora. We propose that this bright component is analogous to the Earth's diffuse aurora.

Mauk, B. H.↗

NASA NTRS2012

Identifying and Evaluating the Relationships that Control a Land Surface Model's Hydrological Behavior

The inherent soil moisture-evaporation relationships used in today 's land surface models (LSMs) arguably reflect a lot of guesswork given the lack of contemporaneous evaporation and soil moisture observations at the spatial scales represented by regional and global models. The inherent soil moisture-runoff relationships used in the LSMs are also of uncertain accuracy. Evaluating these relationships is difficult but crucial given that they have a major impact on how the land component contributes to hydrological and meteorological variability within the climate system. The relationships, it turns out, can be examined efficiently and effectively with a simple water balance model framework. The simple water balance model, driven with multi-decadal observations covering the conterminous United States, shows how different prescribed relationships lead to different manifestations of hydrological variability, some of which can be compared directly to observations. Through the testing of a wide suite of relationships, the simple model provides estimates for the underlying relationships that operate in nature and that should be operating in LSMs. We examine the relationships currently used in a number of different LSMs in the context of the simple water balance model results and make recommendations for potential first-order improvements to these LSMs.

Koster, Randal D.↗

DOE OSTI2023

Enabling a Sustainable Future: Zero-Emission Vehicles Cost Analysis to Inform Decarbonization Pathways

Despite being only 5% of vehicles on the road, medium- and heavy-duty vehicles (MHDVs) are the second largest contributor to transportation emissions (21%) and a major source of local air pollution disproportionally affecting disadvantaged communities. This talk summarizes a cost analysis for zero emissions vehicles (battery electric EVs and hydrogen fuel cell FCEVs) for all medium and heavy duty applications, ranging from large pick-up trucks, to delivery vans, buses, and heavy trucks. Results show that with continued improvements in vehicle and fuel technologies (in line with U.S. Department of Energy targets and vetted with industry), zero-emission vehicles (ZEVs) can reach total-cost-of-driving parity with conventional diesel vehicles by 2035 for all medium- and heavy-duty (MD/HD) vehicle classes without incentives. Assuming economics drives adoption, ZEV sales could reach 42% of all MD/HD trucks by 2030, reflecting lower combined vehicle purchase and operating costs (using real-world payback periods). Two technological solutions - battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs) - are viable in multiple market segments, offering alternative pathways for decarbonization: a) BEVs tend to become cost-competitive for smaller trucks before 2030 and for short-haul (<500-mile) heavy trucks before 2035. b) Hydrogen FCEVs tend to become cost-competitive for long-haul (>500-mile) heavy trucks by 2035. Results are very sensitive to technology improvement trajectories, adoption decision-making, and uncertain assumptions about future freight demand, logistics, and vehicle use explored in multiple scenarios.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

DOE OSTI2020

A Hybrid Stochastic-Interval Operation Strategy for Multi-Energy Microgrids

Increasing deployment of distributed energy resources intensifies interactions among electric, gas, heating, and cooling systems. Inherent uncertainties ranging from internal parameters to external inputs also impose significant challenges on system operation. A coordinated scheduling method is, therefore, desired for facilitating efficient operation of multi-energy microgrids under multiple uncertainties. In this paper, a deterministic coordinated scheduling model is developed first with detailed modeling of system dynamics and device parameters to fully characterize complex interactions among multi-energy carriers. Then, a hybrid stochastic-interval method is proposed to account for heterogeneous uncertainties in decisions of operational strategies. Specifically, performance and efficiency uncertainties of distributed energy resources, and injection uncertainty of renewable sources and multienergy demands are characterized by interval-based uncertain operation regions and probability distributions, respectively. A scenario-based two-stage algorithm is developed to solve the problem so that multiple uncertainties are preserved in the entire decision-making process. Moreover, adjustable operational strategies are determined to hedge uncertainty by considering operators’ risk preferences. The validity of the proposed method is verified by comprehensive case studies on a test system.

hybrid stochastic-interval approach↗

NASA NTRS2017

NASA Human Spaceflight Scenarios - Do All Our Models Still Say No?

Historically, NASA human spaceflight planning has included healthy doses of life cycle cost analysis. Planners put projects and their cost estimates in a budget context. Estimated costs became expected budgets. Regardless, real budgets rarely matched expectations. So plans would come and go as NASA canceled projects. New projects would arise and the cycle would begin again. Repeatedly, NASA schedule and performance ambitions come up against costs growing at double-digit rates while budgets barely rise a couple of percent a year. Significant skepticism greets proposed NASA programs at birth, as cost estimates for new projects are traditionally very high, and worse, far off the mark for those carried forward. In this environment the current "capability driven framework" for NASA human spaceflight evolved, where long term life cycle cost analysis are even viewed as possibly counter-productive. Here, a space exploration project, for example the Space Launch System, focuses on immediate goals. A life cycle is that of a project, not a program, and for only that span of time to a near term milestone like a first test launch. Unfortunately, attempting to avoid some pitfalls in long-term life cycle cost analysis breeds others. Government audits have noted that limiting the scope of cost analysis "does not provide the transparency necessary to assess long-term affordability" making it difficult to understand if NASA "is progressing in a cost-effective and affordable manner." Even in this short-term framework, NASA realizes the importance of long-term considerations, that it must "maximize the efficiency and sustainability of the Exploration Systems development programs", that this is "critical to free resources for re-investment...such as other required deep space exploration capabilities." Assuming the value of long-term life cycle cost analysis, where due diligence meets reconnaissance, and accepting past shortcomings, the work here approaches life cycle cost analysis for human spaceflight differently. 1) If costs have traditionally been so high that adding them up is discouraging, are there any new facts on the ground offering paths to significantly lower costs? 2) If NASA's spaceflight budget and process is an over-arching constraint, with its planning limitations favoring short-term outlooks, is there a way to step outside the budget box? 3) If life cycle answers have historically been too uncertain to be useful, is there a process where stakeholders gain valuable insights merely from emphasizing a common understanding around questions? We analyze the potential life cycle cost of assorted NASA human spaceflight architectures - an architecture as a sum of individual systems, working together. With the prior questions of high costs, limited budgets and uncertainties in mind, public private partnerships are central in these architectures. The cost data for current commercial public private partnerships is encouraging, as are cost estimates for future partnership approaches beyond low Earth orbit. Private capital, directly or indirectly, an ingredient of public private partnerships, may be a significant factor in finding a path around the limits of the NASA spaceflight budget. Also, understanding and reviewing the pros, cons and uncertainties of assorted architectures can assist in developing a common understanding around key questions as important if not more so than the numbers and answers. Lastly, a scenario planning technique is briefly explored that can mature a common understanding about the agencies situation at hand and how diverse stakeholders can go forward together. Scenario planning, rather than focusing on answers, places emphasis on stakeholders developing a common understanding about the future. Putting aside costs, this is especially true of questions about sustainability and growth, results, benefits and expectations. While efficiency exercises or analysis look to reduce resources in one place to apply them elsewhere, moving around slices in a pie, scenario planning can get at the heart of the matter, growing the pie, transforming it, and making the pieces relevant. Especially important is the question of sustainability for different scenarios in the broad sense of the word - not just the narrow ability to survive or continue, but also the ability to adapt, prosper and grow.

space systems life cycle costs↗