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At least 235 records · Page 13

Equipment

A discussion is presented on the problems encountered in designing and constructing a simulator to determine human vestibular response to a range of linear accelerations from 0 to 0.3 g's. Starting with a set of initial performance specifications, the designers combined an array of commercially available components into a system which, altough requiring further refinement before completion, shows considerable promise of fulfilling the initial requirements. The resulting system consists of a wheeled vehicle driven by a cable and drum arrangement, powered by a hydraulic-electric servo-valve. Technical design considerations are presented along with a discussion of the trade-offs between various component options. A description of the system characteristics as well as an analysis of preliminary test results and recommendations for future system improvements are included.

Source record↗

Global Design Optimization for Aerodynamics and Rocket Propulsion Components

Modern computational and experimental tools for aerodynamics and propulsion applications have matured to a stage where they can provide substantial insight into engineering processes involving fluid flows, and can be fruitfully utilized to help improve the design of practical devices. In particular, rapid and continuous development in aerospace engineering demands that new design concepts be regularly proposed to meet goals for increased performance, robustness and safety while concurrently decreasing cost. To date, the majority of the effort in design optimization of fluid dynamics has relied on gradient-based search algorithms. Global optimization methods can utilize the information collected from various sources and by different tools. These methods offer multi-criterion optimization, handle the existence of multiple design points and trade-offs via insight into the entire design space, can easily perform tasks in parallel, and are often effective in filtering the noise intrinsic to numerical and experimental data. However, a successful application of the global optimization method needs to address issues related to data requirements with an increase in the number of design variables, and methods for predicting the model performance. In this article, we review recent progress made in establishing suitable global optimization techniques employing neural network and polynomial-based response surface methodologies. Issues addressed include techniques for construction of the response surface, design of experiment techniques for supplying information in an economical manner, optimization procedures and multi-level techniques, and assessment of relative performance between polynomials and neural networks. Examples drawn from wing aerodynamics, turbulent diffuser flows, gas-gas injectors, and supersonic turbines are employed to help demonstrate the issues involved in an engineering design context. Both the usefulness of the existing knowledge to aid current design practices and the need for future research are identified.

Shyy, Wei↗

Proximity Operations and Docking Sensor Development

The Next Generation Advanced Video Guidance Sensor (NGAVGS) has been under development for the last three years as a long-range proximity operations and docking sensor for use in an Automated Rendezvous and Docking (AR&D) system. The first autonomous rendezvous and docking in the history of the U.S. Space Program was successfully accomplished by Orbital Express, using the Advanced Video Guidance Sensor (AVGS) as the primary docking sensor. That flight proved that the United States now has a mature and flight proven sensor technology for supporting Crew Exploration Vehicles (CEV) and Commercial Orbital Transport Systems (COTS) Automated Rendezvous and Docking (AR&D). NASA video sensors have worked well in the past: the AVGS used on the Demonstration of Autonomous Rendezvous Technology (DART) mission operated successfully in spot mode out to 2 km, and the first generation rendezvous and docking sensor, the Video Guidance Sensor (VGS), was developed and successfully flown on Space Shuttle flights in 1997 and 1998. 12 Parts obsolescence issues prevent the construction of more AVGS units, and the next generation sensor was updated to allow it to support the CEV and COTS programs. The flight proven AR&D sensor has been redesigned to update parts and add additional capabilities for CEV and COTS with the development of the Next Generation AVGS at the Marshall Space Flight Center. The obsolete imager and processor are being replaced with new radiation tolerant parts. In addition, new capabilities include greater sensor range, auto ranging capability, and real-time video output. This paper presents some sensor hardware trades, use of highly integrated laser components, and addresses the needs of future vehicles that may rendezvous and dock with the International Space Station (ISS) and other Constellation vehicles. It also discusses approaches for upgrading AVGS to address parts obsolescence, and concepts for minimizing the sensor footprint, weight, and power requirements. In addition, the testing of the brassboard and proto-type NGAVGS units will be discussed along with the use of the NGAVGS as a proximity operations and docking sensor.

Howard, Richard T.↗

Lessons Learned from the Clementine Mission

According to BMDO, the Clementine mission achieved many of its technology objectives during its flight to the Moon in early 1994 but, because of a software error, was unable to test the autonomous tracking of a cold target. The preliminary analyses of the returned lunar data suggest that valuable scientific measurements were made on several important topics but that COMPLEX's highest-priority objectives for lunar science were not achieved. This is not surprising given that the rationale for Clementine was technological rather than scientific. COMPLEX lists below a few of the lessons that may be learned from Clementine. Although the Clementine mission was not conceived as a NASA science mission exactly like those planned for the Discovery program, many operational aspects of the two are similar. It is therefore worthwhile to understand the strengths and faults of the Clementine approach. Some elements of the Clementine operation that led to the mission's success include the following: (1) The mission's achievements were the responsibility of a single organization and its manager, which made that organization and that individual accountable for the final outcome; (2) The sponsor adopted a hands-off approach and set a minimum number of reviews (three); (3) The sponsor accepted a reasonable amount of risk and allowed the project team to make the trade-offs necessary to minimize the mission's risks while still accomplishing all its primary objectives; and (4) The development schedule was brief and the agreed-on funding (and funding profile) was adhered to. Among the operational shortcomings of Clementine were the following: (1) An overly ambitious schedule and a slightly lean budget (meaning insufficient time for software development and testing, and leading ultimately to human exhaustion); and (2) No support for data calibration, reduction, and analysis. The principal lesson to be learned in this category is that any benefits from the constructive application of higher risk for lower cost and faster schedule will be lost if the schedule does not allow adequate time for the development of all essential systems or makes no allowance for human frailties. Another lesson to be drawn is that despite its limitations, if judged strictly as a science mission, Clementine attested that significant scientific information can be gathered during a technology-demonstration mission. In the current era of limited funds, when science missions will be infrequent, the opportunity to fly scientific instruments aboard missions whose objectives might be other than science must be seized and, indeed, encouraged. During such opportunities it would be inexcusable to do second-class science. Thus the scientific community must be actively involved in such projects from their initiation.

Source record↗

Next Generation Advanced Video Guidance Sensor

The first autonomous rendezvous and docking in the history of the U.S. Space Program was successfully accomplished by Orbital Express, using the Advanced Video Guidance Sensor (AVGS) as the primary docking sensor. The United States now has a mature and flight proven sensor technology for supporting Crew Exploration Vehicles (CEV) and Commercial Orbital Transport. Systems (COTS) Automated Rendezvous and Docking (AR&D). AVGS has a proven pedigree, based on extensive ground testing and flight demonstrations. The AVGS on the Demonstration of Autonomous Rendezvous Technology (DART)mission operated successfully in "spot mode" out to 2 km. The first generation rendezvous and docking sensor, the Video Guidance Sensor (VGS), was developed and successfully flown on Space Shuttle flights in 1997 and 1998. Parts obsolescence issues prevent the construction of more AVGS. units, and the next generation sensor must be updated to support the CEV and COTS programs. The flight proven AR&D sensor is being redesigned to update parts and add additional. capabilities for CEV and COTS with the development of the Next, Generation AVGS (NGAVGS) at the Marshall Space Flight Center. The obsolete imager and processor are being replaced with new radiation tolerant parts. In addition, new capabilities might include greater sensor range, auto ranging, and real-time video output. This paper presents an approach to sensor hardware trades, use of highly integrated laser components, and addresses the needs of future vehicles that may rendezvous and dock with the International Space Station (ISS) and other Constellation vehicles. It will also discuss approaches for upgrading AVGS to address parts obsolescence, and concepts for minimizing the sensor footprint, weight, and power requirements. In addition, parts selection and test plans for the NGAVGS will be addressed to provide a highly reliable flight qualified sensor. Expanded capabilities through innovative use of existing capabilities will also be discussed.

Lee, Jimmy↗

Integration Assessment of Visiting Vehicle Induced Electrical Charging of the International Space Station Structure

The International Space Station (ISS) undergoes electrical charging in low Earth orbit (LEO) due to positively biased, exposed conductors on solar arrays that collect electrical charges from the space plasma. Exposed solar array conductors predominately collect negatively charged electrons and thus drive the metal ISS structure electrical ground to a negative floating potential (FP) relative to plasma. This FP is variable in location and time as a result of local ionospheric conditions. ISS motion through Earth s magnetic field creates an addition inductive voltage up to 20 positive and negative volts across ISS structure depending on its attitude and location in orbit. ISS Visiting Vehicles (VVs), such as the planned Orion crew exploration vehicle, contribute to the ISS plasma charging processes. Upon physical contact with ISS, the current collection properties of VVs combine with ISS. This is an ISS integration concern as FP must be controlled to minimize arcing of ISS surfaces and ensure proper management of extra vehicular activity crewman shock hazards. This report is an assessment of ISS induced charging from docked Orion vehicles employing negatively grounded, 130 volt class, UltraFlex (ATK Space Systems) solar arrays. To assess plasma electron current collection characteristics, Orion solar cell test coupons were constructed and subjected to plasma chamber current collection measurements. During these tests, coupon solar cells were biased between 0 and 120 V while immersed in a simulated LEO plasma. Tests were performed using several different simulated LEO plasma densities and temperatures. These data and associated theoretical scaling of plasma properties, were combined in a numerical model which was integrated into the Boeing Plasma Interaction Model. It was found that the solar array design for Orion will not affect the ISS FP by more than about 2 V during worst case charging conditions. This assessment also motivated a trade study to determine acceptable plasma electron current levels that can be collected by a single or combined fleet of ISS-docked VVs.

Kramer, Leonard↗

Principled Schedulability Analysis for Distributed Storage Systems Using Thread Architecture Models

In this article, we present an approach to systematically examine the schedulability of distributed storage systems, identify their scheduling problems, and enable effective scheduling in these systems. We use Thread Architecture Models (TAMs) to describe the behavior and interactions of different threads in a system, and show both how to construct TAMs for existing systems and utilize TAMs to identify critical scheduling problems. We specify three schedulability conditions that a schedulable TAM should satisfy: completeness, local enforceability, and independence; meeting these conditions enables a system to easily support different scheduling policies. We identify five common problems that prevent a system from satisfying the schedulability conditions, and show that these problems arise in existing systems such as HBase, Cassandra, MongoDB, and Riak, making it difficult or impossible to realize various scheduling disciplines. We demonstrate how to address these schedulability problems using both direct and indirect solutions, with different trade-offs. To show how to apply our approach to enable scheduling in realistic systems, we develop Tamed-HBase and Muzzled-HBase, sets of modifications to HBase that can realize the desired scheduling disciplines, including fairness and priority scheduling, even when presented with challenging workloads.

Computer Science↗

Deep Learning–Assisted Multiobjective Optimization of Geological CO 2 Storage Performance under Geomechanical Risks

In geological CO 2 storage, designing the optimal well control strategy for CO 2 injection to maximize CO 2 storage while minimizing the associated geomechanical risks is not trivial. This challenge arises due to pressure buildup, CO 2 plume migration, the highly nonlinear nature of geomechanical responses to rock-fluid interaction, and the high computational cost associated with coupled flow and geomechanics simulations. In this paper, we introduce a novel optimization framework to address these challenges. The optimization problem is formulated as follows: maximize total CO 2 storage while minimizing geomechanical risks by adjusting the injection schedules within bounded constraints. The geomechanical risks are primarily driven by injection-induced pressure build-up, which is characterized by ground displacement and the induced microseismicity. We used the Fourier neural operator (FNO)-based deep learning model to construct surrogate models, replacing the time-consuming coupled flow and geomechanics simulations for evaluating the aforementioned objective functions. The developed surrogate models have been incorporated into a multiobjective optimization framework through a genetic algorithm to reduce the computational burden. The proposed optimization framework reduces the computational cost from approximately 2,400 hours, when using objective function evaluations based on physics-based simulations, to around 20 minutes. A set of Pareto-optimal solutions of the proposed workflow yields nontrivial optimal decisions, reducing the microseismicity potential and the vertical displacement. This Pareto front highlights the optimal trade-offs between CO 2 storage amount, safety, and ground displacement, emphasizing the need for careful optimization and management of injection strategies to achieve a balanced outcome. The novelty of this work is twofold. First, we demonstrate the importance of incorporating the minimization of the geomechanical risks as objective functions into the CO 2 storage optimization workflow to mitigate the potential risk of induced microseismicity and ground displacement. Second, we leverage the FNO-based surrogate models to optimize a real-field CO 2 storage operation.

42 ENGINEERING↗

A hybrid LBG/lattice vector quantizer for high quality image coding

It is well known that a vector quantizer is an efficient coder offering a good trade-off between quantization distortion and bit rate. The performance of a vector quantizer asymptotically approaches the optimum bound with increasing dimensionality. A vector quantized image suffers from the following types of degradations: (1) edge regions in the coded image contain staircase effects, (2) quasi-constant or slowly varying regions suffer from contouring effects, and (3) textured regions lose details and suffer from granular noise. All three of these degradations are due to the finite size of the code book, the distortion measures used in the design, and due to the finite training procedure involved in the construction of the code book. In this paper, we present an adaptive technique which attempts to ameliorate the edge distortion and contouring effects.

Ramamoorthy, V.↗

Method for Constructing Composite Response Surfaces by Combining Neural Networks with other Interpolation or Estimation Techniques

A method and system for design optimization that incorporates the advantages of both traditional response surface methodology (RSM) and neural networks is disclosed. The present invention employs a unique strategy called parameter-based partitioning of the given design space. In the design procedure, a sequence of composite response surfaces based on both neural networks and polynomial fits is used to traverse the design space to identify an optimal solution. The composite response surface has both the power of neural networks and the economy of low-order polynomials (in terms of the number of simulations needed and the network training requirements). The present invention handles design problems with many more parameters than would be possible using neural networks alone and permits a designer to rapidly perform a variety of trade-off studies before arriving at the final design.

Rai, Man Mohan↗

Interannual variability versus seasonal variability in the tropical Atlantic

Monthly fields of sea surface temperature and wind stress for the tropical Atlantic are constructed for January 1964 to December 1979. Inside the Gulf of Guinea the amplitude of the seasonal variability of SST ranges between 2.5 and 4 times greater than the interannual variability. In the remainder of the equatorial Atlantic this measure is less than 2. Standard deviations of wind stress anomalies indicate that, except near the Intertropical Convergence Zone, the magnitude of interannual fluctuations is greater than that of seasonal ones. The joint analyses of these SST and wind stress fields indicate the largest positive SST anomaly in the Gulf of Guinea (July, 1968) was immediately preceded by the only reversal of the trade winds west along the equator.

Picaut, J.↗

Evaluating and Countering the Insider Threat to the Radioactive Source Supply Chain

The modern supply chain is a global enterprise and little drove this home more than the global COVID-19 pandemic which sent economic shockwaves throughout the world. Many goods became scarce, as products were delayed, in limited supply, or simply not available. The suddenly diminished supply collided with still high demand and led to greatly increased costs. This was particularly true for the radioactive source supply chain. The pandemic introduced extensive delays for construction projects, slowed the transport of radiological materials to facilities, interrupted treatment deliveries, and impaired the mobility of contractors across the industry. All of these concerns not only adversely affected the economy, but also impacted the safety and security of radiological material, potentially raising national security concerns. The vulnerability of the supply chain, a critical element in an increasingly interconnected world, was exposed. One example that challenged the adaptive capacity of the overall supply chain is the Ever Given container ship, which became stuck in the Suez Canal in 2020. This accident immediately shut down shipments that accounted for 12% of global trade, with long-term impacts estimated to be much larger. Developing the ability to anticipate and react in real-time to sudden changes has quickly become a necessity, particularly in industries that deal with the transport of hazardous material. The reaction to these dramatic incidents was to largely focus attention and resources on protecting the supply chain from external threats. However, the threat to the radioactive material supply chain from insiders intimately involved in the process may be even greater and remains a blind spot that requires increased attention. Recent events revealed the blueprint for targeting and disrupting that supply chain, so the potential for a malicious insider—or a manipulated, unwitting insider—to take advantage of this vulnerability is elevated, creating security concerns for radiological industries. This paper examines and analyzes the potential insider threat to the radioactive source supply chain and recommends steps to take to counter this possibility.

Kinney, Justin↗

Satellite Power Systems (SPS) concept definition study (Exhibit D). Volume 4: Operations analyses

Using a coplanar, end-mounted antenna as a baseline, various configuration trades were performed to select a preferred solid state concept. The increase in efficiency that could be realized by use of multi bandgap solar cells, either with klystron or solid state antenna was evaluated. Satellite configurations were developed to exploit the sandwich antenna concept wherein solar cells are located on one side of the antenna panel and solid state dc/RF converters on the other side. These concepts entailed various primary and secondary reflector arrangements for directing solar energy to the solar cell side of the antenna with higher concentration ratios than used on the coplanar configurations. Operations analysis included development of a satellite construction scenario, a concept for the SCB, a top-level satellite construction operation, construction operation, construction timelines and crew sizes, mass flows to orbit, and a satellite maintenance scenario. The list of materials required for satellite construction was updated to identify significant differences relevant to the solid state satellite concept. Means of decommissioning satellites at the end of their design life were studied.

Hanley, G. M.↗

The Spacecraft Materials Selector: An Artificial Intelligence System for Preliminary Design Trade Studies, Materials Assessments, and Estimates of Environments Present

Institutions need ways to retain valuable information even as experienced individuals leave an organization. Modern electronic systems have enough capacity to retain large quantities of information that can mitigate the loss of experience. Performance information for long-term space applications is relatively scarce and specific information (typically held by a few individuals within a single project) is often rather narrowly distributed. Spacecraft operate under severe conditions and the consequences of hardware and/or system failures, in terms of cost, loss of information, and time required to replace the loss, are extreme. These risk factors place a premium on appropriate choice of materials and components for space applications. An expert system is a very cost-effective method for sharing valuable and scarce information about spacecraft performance. Boeing has an artificial intelligence software package, called the Boeing Expert System Tool (BEST), to construct and operate knowledge bases to selectively recall and distribute information about specific subjects. A specific knowledge base to evaluate the on-orbit performance of selected materials on spacecraft has been developed under contract to the NASA SEE program. The performance capabilities of the Spacecraft Materials Selector (SMS) knowledge base are described. The knowledge base is a backward-chaining, rule-based system. The user answers a sequence of questions, and the expert system provides estimates of optical and mechanical performance of selected materials under specific environmental conditions. The initial operating capability of the system will include data for Kapton, silverized Teflon, selected paints, silicone-based materials, and certain metals. For situations where a mission profile (launch date, orbital parameters, mission duration, spacecraft orientation) is not precisely defined, the knowledge base still attempts to provide qualitative observations about materials performance and likely exposures. Prior to the NASA contract, a knowledge base, the Spacecraft Environments Assistant (SEA,) was initially developed by Boeing to estimate the environmental factors important for a specific spacecraft mission profile. The NASA SEE program has funded specific enhancements to the capability of this knowledge base. The SEA qualitatively identifies over 25 environmental factors that may influence the performance of a spacecraft during its operational lifetime. For cases where sufficiently detailed answers are provided to questions asked by the knowledge base, atomic oxygen fluence levels, proton and/or electron fluence and dose levels, and solar exposure hours are calculated. The SMS knowledge base incorporates the previously developed SEA knowledge base. A case history for previous flight experiment will be shown as an example, and capabilities and limitations of the system will be discussed.

Pippin, H. G.↗

Improved Spacecraft Materials for Radiation Protection

Methods by which radiation shielding is optimized need to be developed and materials of improved shielding characteristics identified and validated. The galactic cosmic rays (GCR) are very penetrating and the energy absorbed by the astronaut behind the shield is nearly independent of shield composition and even the shield thickness. However, the mix of particles in the transmitted beam changes rapidly with shield material composition and thickness. This results in part from the breakup of the high-energy heavy ions of the GCR which make contributions to biological effects out of proportion to their deposited energy. So the mixture of particles in the radiation field changes with shielding and the control of risk contributions from dominant particle types is critical to reducing the hazard to the astronaut. The risk of biological injury for a given particle type depends on the type of biological effect and is specific to cell or tissue type. Thus, one is faced with choosing materials which may protect a given tissue against a given effect but leave unchanged or even increase the risk of other effects in the same tissue or increase the risks to other adjacent tissues of a different type in the same individual. The optimization of shield composition will then be tied to a specific tissue and risk to that tissue. Such peculiarities arise from the complicated mixture of particles, the nature of their biological response, and the details of their interaction with material constituents. Aside from the understanding of the biological response to specific components, one also needs an accurate understanding of the radiation emerging from the shield material. This latter subject has been a principal element of this project. In the past ten years our understanding of space radiation interactions with materials has changed radically, with a large impact on shield design. For example, the NCRP estimated that only 2 g/sq cm. of aluminum would be required to meet the annual 500 mSv limit for the exposure of the blood forming organs (this limit is strictly for LEO but can be used as a guideline for the Mars mission analysis). The current estimates require aluminum shield thicknesses above 50 g/sq cm., which is impractical. In such a heavily shielded vehicle, the neutrons produced throughout the vehicle also contribute significantly to the exposure and this demands greater care in describing the angular dependence of secondary particle production processes. As such the continued testing of databases and transport procedures in laboratory and spaceflight experiments has continued. This has been the focus of much of the last year's activity and has resulted in improved neutron prediction capability. These new methods have also improved our understanding of the surface environment of Mars. The Mars 2003 NRA HEDS related surface science requirements were driven by the need to validate predictions on the upward flux of neutrons produced in the Martian regolith and bedrock made by the codes developed under this project. The codes used in the surface environment definition are also being used to look at in situ resources for the development of construction material for Martian surface facilities. For example, synthesis of polyimides and polyethylene as binders of regolith for developing basic structural elements has been studied and targets built for accelerator beam testing of radiation shielding properties. Preliminary mechanical tests have also been promising. Improved spacecraft materials have been identified (using the criteria reported by this project at the last conference) as potentially important for future shielding materials. These are liquid hydrogen, hydrogenated nanofibers, liquid methane, LiH, Polyethylene, Polysulfone, and Polyetherimide (in order of decreasing shield performance). Some of the materials are multifunctional and are required for other onboard systems. We are currently preparing software for trade studies with these materials relative to the Mars Reference Mission as required in the project's final year.

Wilson, John W.↗

Two-Tower Quantum Matrix Chain Multiplication: Trading Qubits for Depth

Matrix chain multiplication -- computing $\mathcal{W} = M^{(0)}\cdots M^{(K-1)}$ where $M^{(k)} \in \mathbb{R}^{P_k \times P_{k+1}}$-- arises in scientific computing, machine learning, and graph analysis. Despite the importance of this problem, for chains of distinct matrices, the classical number of operations grows linearly with the chain length $K$ and polynomially in the matrix dimensions. We present \emph{Two-Tower Matrix Multiplication}, a quantum subroutine that encodes the product $\mathcal{W}$ of the $K$ matrices into a quantum state in circuit depth $\mathcal{O}(\max_{k} \mathrm{polylog} (P_k P_{k+1}))$, which is independent of~$K$ within the QRAM-based state-preparation model, whereas the qubit count is $\mathcal{O}\bigl(\sum_{k} \log P_k \bigr)$; the total gate count remains linear in $K$, so the gain is in the circuit depth. The construction interleaves state-preparation operators across two layers; within each layer, all operators act on disjoint registers and execute in parallel. This subroutine can be specialized for the chain-vector case, which computes the product of $K-1$ matrices applied to a vector. We prove the correctness of the subroutine for all $K$ and provide two implementations using the Qiskit and QCLAB frameworks. The subroutine is applicable to any downstream quantum algorithm that operates on a matrix encoded in the statevector, including norm estimation, graph-matrix powers, linear system solving, and quantum machine learning kernels.

Antonioli, Giacomo [Pisa U.] (ORCID:00090000668703↗

Experimental Optimization of a Free-to-Rotate Wing for Small UAS

This paper discusses an experimental investigation conducted to optimize a free-to-rotate wing for use on a small unmanned aircraft system (UAS). Although free-to-rotate wings have been used for decades on various small UAS and small manned aircraft, little is known about how to optimize these unusual wings for a specific application. The paper discusses some of the design rationale of the basic wing. In addition, three main parameters were selected for "optimization", wing camber, wing pivot location, and wing center of gravity (c.g.) location. A small apparatus was constructed to enable some simple experimental analysis of these parameters. A design-of-experiment series of tests were first conducted to discern which of the main optimization parameters were most likely to have the greatest impact on the outputs of interest, namely, some measure of "stability", some measure of the lift being generated at the neutral position, and how quickly the wing "recovers" from an upset. A second set of tests were conducted to develop a response-surface numerical representation of these outputs as functions of the three primary inputs. The response surface numerical representations are then used to develop an "optimum" within the trade space investigated. The results of the optimization are then tested experimentally to validate the predictions.

Logan, Michael J.↗

Carbon Capture, Transport, And Storage (CTS) Cost Modeling Of The Onshore Gulf Coast

The onshore Gulf of Mexico region presents significant opportunities for CO2 capture, transport, and storage due to its numerous CO2 sources, such as power plants, refineries, and its substantial CO2 storage potential. However, operators face critical decisions in designing an efficient and cost-effective CO2 pipeline network. This study examines the economic implications of two primary strategies: constructing a trunkline with excess initial capacity versus developing dedicated pipelines incrementally as new CO2 sources come online. Building a trunkline first offers the advantage of future-proofing the network, allowing for the accommodation of increased CO2 volumes from various sources over time. However, this approach incurs higher upfront costs and risks underutilizing the transport capacity in the initial stages, potentially resulting in economic inefficiencies. Conversely, constructing dedicated pipelines for each new CO2 source as it becomes operational may avoid the initial overcapacity issue but fails to capitalize on the economies of scale. This could lead to higher overall costs due to the duplication of infrastructure and increased complexity in network management. This research employs a comprehensive cost-benefit analysis, integrating factors such as capital expenditure, operational costs, projected CO2 volumes, and potential economies of scale. Through this analysis, we aim to provide operators with insights into the most economically viable strategy for CO2 pipeline network design in the region. The findings underscore the importance of strategic planning and highlight the trade-offs between immediate capacity utilization and long-term cost savings, ultimately guiding stakeholders towards informed decision-making in the development of CO2 transport infrastructure. Presented at the 41st USAEE/IAEE North American Conference, 3-6 November 2024, Baton Rouge, LA, United States.

Shih, Chung Yan↗