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Dynamics and Control of a Disordered System in Space

In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of N grains in orbit, with N greater than 10(exp 3). These grains can be large (Cubesat-size) or small (mm-size), and can be active, i.e., a fully equipped vehicle capable sensing their own position and attitude, and enabled with propulsion means, or entirely passive. The ultimate objective would be to study the behavior of the single grains and of large ensembles of grains in orbit and to identify ways to guide and control the shape of a cloud composed of these grains so that it can perform a useful function in space, for instance, as an element of an optical imaging system for astrophysical applications. This concept, in which the aperture does not need to be continuous and monolithic, would increase the aperture size several times compared to large NASA observatories such as ATLAST, allowing for a true Terrestrial Planet Imager that would be able to resolve exo-planet details and do meaningful spectroscopy on distant world. In the paper, we address the modeling and autonomous operation of a distributed assembly (the cloud) of large numbers of highly miniaturized space-borne elements (the grains). A multi-scale, multi-physics model is proposed of the dynamics of the cloud in orbit, as well as a control law for cloud shape maintenance, and preliminary simulation studies yield an estimate of the computational effort, indicating a scale factor of approximately N(exp 1.4) as a function of the number of grains. A granular spacecraft can be defined as a collection of a large number of space-borne elements (in the 1000s) designed and controlled such that a desirable collective behavior emerges, either from the interactions among neighboring grains, and/or between the grains and the environment. In this paper, each grain is considered to be a highly miniaturized spacecraft which has limited size and mass, hence it has limited actuation, limited propulsive capability, limited power, limited sensing, limited communication, limited computational resources, limited range of motion, limited lifetime, and may be expendable. The modeling and dynamics of clouds of vehicles is more challenging than with conventional vehicles because we are faced with a probabilistic vehicle composed of a large number of physically disconnected vehicles. First, different scales of motion occur simultaneously in a cloud: translations and rotations of the cloud as a whole (macro-dynamics), relative rotation and translation of one cloud member with respect to another (meso-dynamics), and individual cloud member dynamics (micro-dynamics). Second, the control design needs to be tolerant of the system complexity, of the system architecture (centralized vs. decentralized large scale system control) as well as robust to un-modeled dynamics and noise sources. Figure 1, top left, shows the kinematic parameters of a 1000 element cloud in orbit. The motion of the system is described with respect to a local vertical-local horizontal (LV-LH) orbiting reference frame (x,y,z)=F(sub ORF) of origin O(sub ORF) which rotates with mean motion omega and orbital semi-major axis R(sub 0). The orbital geometry at the initial time is defined in terms of its six orbital elements, and the orbital dynamics equation for point O(sub ORF) is propagated forward in time under the influence of the gravitational field of the primary and other external perturbations, described below. The origin of this frame coincides with the initial position of the center of mass of the system, and the coordinate axes are z along the local vertical, x toward the flight direction, and y in the orbit normal direction. The assumptions we used to model the dynamics are as follows: 1) The inertial frame is fixed at Earth's center. 2) The orbiting Frame ORF follows Keplerian orbit. 3) the cloud system dynamics is referred to ORF. 4) the attitude of each grain uses the principal body frame as body fixed frame. 5) the atmosphere is assumed to be rigidly rotating with the Earth. Regarding the grains forming the cloud: 1) each grain is modeled as a rigid body; 2) a simple attitude estimator provides attitude estimates, 3) a simple guidance logic commands the position and attitude of each grain, 4) a simple local feedback controller based on PD control of local states is used to stabilize the attitude of the vehicle. Regarding the cloud: 1) the cloud as a whole is modeled as an equivalent rigid body in orbit, and 2) an associated graph establishes agent connectivity and enables coupling between modes of motion at the micro and macro scales; 3) a simple guidance and estimation logic is modeled to estimate and command the attitude of this equivalent rigid body; 4) a cloud shape maintenance controller is based on the dynamics of a stable virtual truss in the orbiting frame. Regarding the environmental perturbations acting on the cloud: 1) a non-spherical gravity field including JO (Earth's spherical field) zonal component, J2 (Earth's oblateness) and J3 zonal components is implemented; 2) atmospheric drag is modeled with an exponential model; 3) solar pressure is modeled assuming the Sun is inertially fixed; and 4) the Earth's magnetic field is model using an equivalent dipole model. The equations of motion are written in a referential system with respect to the origin of the orbiting frame and the state is propagated forward in time using an incremental predictor-corrector scheme. A representative cloud with varying number of grains is simulated to identify the limitations in computation time as the number of grains grows. We derive a control law to track a desired surface in the ORF (equivalently to maintain a reference cloud shape) by defining an error from a desired surface shape, and designing a control law that is exponentially stable and reduces the tracking error to zero. Figure 1 (top right) shows a comparison of various requirements for simulation of single spacecraft vs. granular spacecraft, indicating the high degree of complexity that needs to be taken into consideration. The ORF components of control force required by one of the grains is, for this particular case, in the micro-Newton range. However, no attempt has been made yet to reconfigure (or re-orient) the cloud configuration internally, for which forces in the milli-Newton level are expected, depending on the time required to do the reconfiguration. Figure 1, bottom, shows the computation time as a function of the number of grains, indicating an order N(exp 1.43) scaling on a 8 Gb, 1067 MHz RAM MacOSX computer with a 3.06 GHz Intel Core 2 Duo processor. With this metric, the same simulation for a system of N=1000 grains would take 5.4 hours, and 146 hours (i.e., 6 days) for a system with N=10,000 grains. Therefore, efficient ways to simulate this complex system, where not only the time scales of natural system dynamics, but also the sampling times of the Guidance, Navigation, and Control are included, remain to be explored. Additional details on the cloud modeling, dynamics, and control will be described in the paper.

simulation↗

Site Selection for Mars Exopaleontology in 2001

The microbial fossil record encompasses a wide range of information, including cellular remains, stromatolites, biofabrics, trace fossils, biominerals and chemofossils. The preservation of fossils is strongly influenced by the physical, chemical and biological factors of the environment which, acting together, ultimately determine the types of information that will be captured and retained in the rock record. The critical factor in assessing the suitability of a site for a microbial fossil record is the paleoenvironment. The reconstruction of ancient sedimentary environments usually requires the integration of a wide variety of geological information, including the shape, geometry and internal structure of sedimentary deposits, their mineralogy, and geochemistry. For Mars, much of our knowledge about past environments is based on orbital imaging of geomorphic features. This evidence provides an important context and starting point for site selection. However, our knowledge of the martian surface is quite limited, and a major goal of the upcoming exploration effort is to reconstruct the history of Martian volatiles, climate, and hydrology as a context for the exploration for past or present life. Mineralogical mapping from orbit will be an important key in this effort. In exploring for evidence of past life, terrestrial experience suggests that the long-term preservation of biological information as fossils occurs under a fairly narrow range of geological conditions that are well known to paleontologists (1). In detrital sedimentary systems, microbial fossilization is favored by rapid burial in fine-grained, clay-rich sediments. In chemical sedimentary systems, preservation is enhanced by rapid entombment in fine-grained chemical precipitates. For long term preservation, host rocks must be composed of stable minerals that resist chemical weathering, and which form an impermeable matrix and closed chemical system that can protect biosignatures from alteration during subsequent diagenetic change or metamorphism. In this context, host rocks composed of highly ordered, chemically-stable mineral phases, like silica (forming cherts) or phosphate (forming phosphorites), are especially favored. Such lithologies tend to have very long crustal residence times and (along with carbonates and shales), are the most common host rocks for the Precambrian microfossil record on Earth. If we assume that a subsurface hydrosphere has been present throughout martian history, then life could have originated there at any time, perhaps emerging at the surface periodically when climate changes, induced by external forcing or endogenous processes (e.g. volcanism), allowed liquid water to exist at the surface. The recent discovery of subsurface chemolithoautotrophic organisms which are capable of synthesizing organic substrates from C02 and H2 liberated from the aqueous weathering of basalt, is especially. relevant as a model for martian life. While a subsurface habitable zone may yet exist on Mars, access to such environments will likely require drilling to depths of several kilometers. Given the technological challenge of deep drilling, this is unlikely to occur prior to human missions. So, even if there is extant life on Mars today in subsurface habitats, it may be much easier to find its fossil counterparts in ancient deposits exposed at the surface. In exploring for a fossil record in subsurface environments on Mars there are several geological situations that may provide access to the appropriate materials. These include 1) ejecta from impact craters, 2) talus slopes, debris flows or alluvial fans developed below the walls of deep canyons, and 3) the deposits of outflood channels. Examples of aqueous mineral deposits of formed in subsurface environments that could harbor a microbial fossil record include such things as cements in detrital sedimentary rocks, low temperature diagenetic minerals deposited in veins, or filling vesicles in volcanic rocks, and hydrothermal deposits formed below the upper temperature limit for life (about 160 degrees C). There are many sites within the present latitudinal constraints for the 2001 mission (15 deg S to 30 deg N) that meet these requirements. But the practical problem with these kinds of deposits is that they tend to be disseminated, making up only a small percentage of a host rock. Even with mineralogical information provided by the Thermal Emission Spectrometer (TES) presently in orbit around Mars, predicting their occurrence ahead of time may be quite difficult. The deposits of surficial aqueous sedimentary systems are likely to provide the largest targets for site selection in 2001. Of these, the deposits of hydrothermal systems (subaerial and subaqueous thermal springs) have been discussed previously. It is likely that hydrothermal systems were widespread on Mars early in its history and a number of common geo-tectonic settings on Mars are likely to have hosted hydrothermal activity. Most of these are represented within the latitudinal constraints presently identified for 2001. However, the deposits of surface spring systems are likely to be difficult to find as well. On Earth, exposure areas for hydrothermal spring mounds are typically a few square kms, less than a single TES pixel. But such deposits may be quite abundant within some volcanic terrains, It is estimated, for example, that between 15-20% of the floor of Yellowstone caldera is covered by thermal spring deposits. In such abundances, subaerial sinters could well be detected by TES. Where exposed, the shallow subsurface portions of these systems may be quite a lot larger (perhaps tens of square kms), although (as noted above) mineralization may be finely disseminated in the basement rock, making remote detection more difficult. Paleolake Basins. There are a large number of potential paleolake basins on Mars (inclusive of impact craters and volcanic calderas) that have been previously identified using Viking images. Most of these lie in the southern highlands beyond the l5 deg S constraint for 2001. However, deposits of paleolakes may offer the largest and most easily identified exopaleontological targets from orbit. Based on a variety of arguments, some workers have suggested that there was once an ancient ocean on the northern plains, and some sites of interest (potential shoreline terraces) fall within the 30 deg N constraint. From a paleontological standpoint the most interesting places of this type are terminal paleolake basins which are likely to have been both saline and alkaline. Models by Schaefer suggest such environments could be widespread on Mars. The conditions in terminal lake basin settings favor widespread chemical sedimentation, an important condition for microbial fossilization. Important lithological targets for a microbial fossil record in terminal lake basins include spring-deposited carbonates, shoreline cements, a wide variety of evaporite minerals and fine-grained detrital sediments including shales, marls, and water-lain volcanic ash deposits. In developing a strategy to explore for ancient hydrothermal deposits on Mars, we can learn from the methods that have been developed by explorationists to explore for economic mineral deposits on Earth. Due to their simple mineralogy, hydrothermal deposits can often be detected using remote sensing methods. Common thermal spring mineral assemblages include silica, carbonate, and various metallic oxides and sulfides. But there are also a number of diagnostic silicate minerals, including clays, formed by the hydrothermal alteration of country rocks. These hydrothermal minerals have characteristic spectral signatures that could be detected from Mars orbit using high resolution infrared remote sensing methods. In playa lake settings, evaporite deposits often form a predictable "bull's eye" pattern with carbonates being deposited in marginal basin areas, and sulfates and halides occurring progressively more basinward. The floors of some impact craters on Mars, such as "White Rock" and Bequeral Crater (see Oxia Palus NE, Site 148), have floor deposits that could be evaporites, inclusive of carbonates. Evaporite minerals possess characteristic spectral signatures in the infrared and could similarly be identified from Mars orbit using high resolution remote sensing methods. Clearly, utilization of TES data will be important for optimizing site selection for Exopaleontology, and every effort should be made to benefit from that data before a final decision is made.

Farmer, Jack↗

Global Methane Budget 2000–2020

Abstract. Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. CH4 is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2), and both emissions and atmospheric concentrations of CH4 have continued to increase since 2007 after a temporary pause. The relative importance of CH4 emissions compared to those of CO2 for temperature change is related to its shorter atmospheric lifetime, stronger radiative effect, and acceleration in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in quantifying the factors responsible for the observed atmospheric growth rate arise from diverse, geographically overlapping CH4 sources and from the uncertain magnitude and temporal change in the destruction of CH4 by short-lived and highly variable hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to improve, synthesise, and update the global CH4 budget regularly and to stimulate new research on the methane cycle. Following Saunois et al. (2016, 2020), we present here the third version of the living review paper dedicated to the decadal CH4 budget, integrating results of top-down CH4 emission estimates (based on in situ and Greenhouse Gases Observing SATellite (GOSAT) atmospheric observations and an ensemble of atmospheric inverse-model results) and bottom-up estimates (based on process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). We present a budget for the most recent 2010–2019 calendar decade (the latest period for which full data sets are available), for the previous decade of 2000–2009 and for the year 2020. The revision of the bottom-up budget in this 2025 edition benefits from important progress in estimating inland freshwater emissions, with better counting of emissions from lakes and ponds, reservoirs, and streams and rivers. This budget also reduces double counting across freshwater and wetland emissions and, for the first time, includes an estimate of the potential double counting that may exist (average of 23 Tg CH4 yr−1). Bottom-up approaches show that the combined wetland and inland freshwater emissions average 248 [159–369] Tg CH4 yr−1 for the 2010–2019 decade. Natural fluxes are perturbed by human activities through climate, eutrophication, and land use. In this budget, we also estimate, for the first time, this anthropogenic component contributing to wetland and inland freshwater emissions. Newly available gridded products also allowed us to derive an almost complete latitudinal and regional budget based on bottom-up approaches. For the 2010–2019 decade, global CH4 emissions are estimated by atmospheric inversions (top-down) to be 575 Tg CH4 yr−1 (range 553–586, corresponding to the minimum and maximum estimates of the model ensemble). Of this amount, 369 Tg CH4 yr−1 or ∼ 65 % is attributed to direct anthropogenic sources in the fossil, agriculture, and waste and anthropogenic biomass burning (range 350–391 Tg CH4 yr−1 or 63 %–68 %). For the 2000–2009 period, the atmospheric inversions give a slightly lower total emission than for 2010–2019, by 32 Tg CH4 yr−1 (range 9–40). The 2020 emission rate is the highest of the period and reaches 608 Tg CH4 yr−1 (range 581–627), which is 12 % higher than the average emissions in the 2000s. Since 2012, global direct anthropogenic CH4 emission trends have been tracking scenarios that assume no or minimal climate mitigation policies proposed by the Intergovernmental Panel on Climate Change (shared socio-economic pathways SSP5 and SSP3). Bottom-up methods suggest 16 % (94 Tg CH4 yr−1) larger global emissions (669 Tg CH4 yr−1, range 512–849) than top-down inversion methods for the 2010–2019 period. The discrepancy between the bottom-up and the top-down budgets has been greatly reduced compared to the previous differences (167 and 156 Tg CH4 yr−1 in Saunois et al. (2016, 2020) respectively), and for the first time uncertainties in bottom-up and top-down budgets overlap. Although differences have been reduced between inversions and bottom-up, the most important source of uncertainty in the global CH4 budget is still attributable to natural emissions, especially those from wetlands and inland freshwaters. The tropospheric loss of methane, as the main contributor to methane lifetime, has been estimated at 563 [510–663] Tg CH4 yr−1 based on chemistry–climate models. These values are slightly larger than for 2000–2009 due to the impact of the rise in atmospheric methane and remaining large uncertainty (∼ 25 %). The total sink of CH4 is estimated at 633 [507–796] Tg CH4 yr−1 by the bottom-up approaches and at 554 [550–567] Tg CH4 yr−1 by top-down approaches. However, most of the top-down models use the same OH distribution, which introduces less uncertainty to the global budget than is likely justified. For 2010–2019, agriculture and waste contributed an estimated 228 [213–242] Tg CH4 yr−1 in the top-down budget and 211 [195–231] Tg CH4 yr−1 in the bottom-up budget. Fossil fuel emissions contributed 115 [100–124] Tg CH4 yr−1 in the top-down budget and 120 [117–125] Tg CH4 yr−1 in the bottom-up budget. Biomass and biofuel burning contributed 27 [26–27] Tg CH4 yr−1 in the top-down budget and 28 [21–39] Tg CH4 yr−1 in the bottom-up budget. We identify five major priorities for improving the CH4 budget: (i) producing a global, high-resolution map of water-saturated soils and inundated areas emitting CH4 based on a robust classification of different types of emitting ecosystems; (ii) further development of process-based models for inland-water emissions; (iii) intensification of CH4 observations at local (e.g. FLUXNET-CH4 measurements, urban-scale monitoring, satellite imagery with pointing capabilities) to regional scales (surface networks and global remote sensing measurements from satellites) to constrain both bottom-up models and atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) integration of 3D variational inversion systems using isotopic and/or co-emitted species such as ethane as well as information in the bottom-up inventories on anthropogenic super-emitters detected by remote sensing (mainly oil and gas sector but also coal, agriculture, and landfills) to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GKQ9-2RHT (Martinez et al., 2024).

54 ENVIRONMENTAL SCIENCES↗