Storage Pipelines Research Articles

SG-LPR: Semantic-Guided LiDAR-Based Place Recognition

Place recognition plays a crucial role in tasks such as loop closure detection and re-localization in robotic navigation. As a high-level representation within scenes, semantics enables models to effectively distinguish geometrically similar places, therefore enhancing their robustness to environmental changes. Unlike most existing semantic-based LiDAR place recognition (LPR) methods that adopt a multi-stage and relatively segregated data-processing and storage pipeline, we propose a novel end-to-end LPR model guided by semantic information—SG-LPR. This model introduces a semantic segmentation auxiliary task to guide the model in autonomously capturing high-level semantic information from the scene, implicitly integrating these features into the main LPR task, thus providing a unified framework of “segmentation-while-describing” and avoiding additional intermediate data-processing and storage steps. Moreover, the semantic segmentation auxiliary task operates only during model training, therefore not adding any time overhead during the testing phase. The model also combines the advantages of Swin Transformer and U-Net to address the shortcomings of current semantic-based LPR methods in capturing global contextual information and extracting fine-grained features. Extensive experiments conducted on multiple sequences from the KITTI and NCLT datasets validate the effectiveness, robustness, and generalization ability of our proposed method. Our approach achieves notable performance improvements over state-of-the-art methods.

Optimizing large-scale hydrogen storage: A novel hybrid genetic algorithm approach for efficient pipeline network design

As hydrogen production technologies continue to advance, efficient and high-capacity hydrogen storage solutions become increasingly crucial. To address the complex optimization challenges in the design of large-scale hydrogen storage pipeline networks, the study introduces a mixed integer nonlinear optimization model inspired by hydrogen pipeline design optimization theory. The model not only focuses on optimizing network design parameters but also aims to minimize investment costs. To achieve this, the study proposes an innovative hybrid genetic algorithm that combines the Modified Feasible Directions Method (MFDM) and Genetic Algorithm Theory (GAT), specifically targeting the optimization of pipeline diameter's discrete distribution challenges. Comparative analyses with SUMT and GA algorithms demonstrate the superiority of the approach. In continuous space, the algorithm achieves a lower convergence cost of 232.4437 × 104 Yuan, while in discrete space, the cost further decreases to 212.1636 × 104 Yuan. Additionally, the study delves into the sensitivity of the HGA-MFDM algorithm to ambient temperature and wellhead temperature in hydrogen storage facilities. The analysis reveals that wellhead temperature has a more significant impact on pipeline network investment, whereas ambient temperature exhibits a more pronounced effect on iteration curves. The findings provide valuable insights for the precise adjustment and optimization of hydrogen storage pipeline networks in practical applications.

Performance Research and Application Progress of Thermal Insulation Materials for Cold Storage

The thermal insulation performance of thermal insulation materials for cold storage has a great influence on the energy saving of cold storage, so many scholars have done a lot of research on it. This paper summarizes the production, application, and performance analysis of Polyurethane foam plastics (PU), Expanded polystyrene (EPS), Extruded polystyrene (XPS), and rock wool for cold storage, and summarizes the thermal insulation application of civil-type cold storage, steel structure cold storage, prefabricated cold storage and cold storage pipeline, as well as the cold storage anti-cold bridge measures.

Identification of slug flow in underwater compressed gas energy storage pipeline using pressure signals

Identification of slug flow in underwater compressed gas energy storage pipeline using pressure signals

Integrating FPGA Acceleration in the DNAssim Framework for Faster DNA-Based Data Storage Simulations

DNA-based data storage emerged in this decade as a promising solution for long data durability, low power consumption, and high density. However, such technology has not yet reached a good maturity level, requiring many investigations to improve the information encoding and decoding processes. Simulations can be key to overcoming the time and the cost burdens of the many experiments imposed by thorough design space explorations. In response to this, we have developed a DNA storage simulator (DNAssim) that allows simulating the different steps in the DNA storage pipeline using a proprietary software infrastructure written in Python/C language. Among the many operations performed by the tool, the edit distance calculation used during clustering operations has been identified as the most computationally intensive task in software, thus calling for hardware acceleration. In this work, we demonstrate the integration in the DNAssim framework of a dedicated FPGA hardware accelerator based on the Xilinx VC707 evaluation kit to boost edit distance calculations by up to 11 times with respect to a pure software approach. This materializes in a clustering simulation latency reduction of up to 5.5 times and paves the way for future scale-out DNA storage simulation platforms.

Towards Migration-Free "Just-in-Case" Data Archival for Future Cloud Data Lakes Using Synthetic DNA

Given the growing adoption of AI, cloud data lakes are facing the need to support cost-effective "just-in-case" data archival over long time periods to meet regulatory compliance requirements. Unfortunately, current media technologies suffer from fundamental issues that will soon, if not already, make cost-effective data archival infeasible. In this paper, we present a vision for redesigning the archival tier of cloud data lakes based on a novel, obsolescence-free storage medium-synthetic DNA. In doing so, we make two contributions: (i) we highlight the challenges in using DNA for data archival and list several open research problems, (ii) we outline OligoArchive-DSM (OA-DSM)-an end-to-end DNA storage pipeline that we are developing to demonstrate the feasibility of our vision.

Design and Selection of Pipelines for Compressed Air Energy Storage Power Plants

The principle of Compressed-air energy storage is that the compressed air energy storage system uses compressed air as the energy storage carrier, which is a physical Energy storage that uses mechanical equipment to realize energy storage, transfer and utilization across time and space. At present, Compressed-air energy storage is the second largest technology that is considered suitable for GW level large-scale electric energy storage after pumped storage. Compressed air energy storage has outstanding advantages such as large scale, low cost, long service life, and short construction period. As a key link connecting compressors, expanders, and gas storage devices, the compressed air main pipeline has characteristics such as high operating pressure, low internal fluid temperature, large temperature difference between indoor and outdoor pipelines, and frequent start and stop. The design, calculation, and installation of the compressed air main pipeline will affect the economy and reliability of the entire system, and even bring serious destructive accidents. This article comprehensively introduces the selection method and process of compressed air energy storage pipeline design, and further verifies the feasibility and accuracy of the design method through case studies of specific projects. It provides convenience and calculation methods for the large-scale development of compressed air energy storage projects in the future[1].

Research on thermal insulation performance of composite energy storage pipeline with phase change materials

The oil and gas pipeline transportation technology is the key to the surface production of oil field, and the pipeline insulation technology plays an important role in realizing the safe, stable and energy-saving transportation of crude oil. The composite energy storage pipeline with PCM not only has thermal insulation performance, but also can greatly prolong the safe shutdown time when the shutdown condition occurs by taking advantage of the storage and discharge energy characteristics of PCM. In this paper, the reasonable structural parameters of composite energy storage pipeline with PCM were determined by comparing the effective insulation time of three typical pipelines under the same working conditions and combining with thermal resistance method. Considering the nonlinear latent heat release and phase change characteristics of crude oil, a pipe-PCM-oil coupling thermodynamic model was established for the composite insulation pipeline, and numerical solution was carried out. The heat transfer characteristics of composite energy storage pipeline with PCM under different working conditions were analyzed, and the effects of physical properties and structures of different PCM on the thermal insulation performance of composite energy storage pipeline were compared. The research results can provide theoretical support for the safe shutdown scheme of oil pipeline.

Dimension optimization for underground natural gas storage pipeline network coupling injection and production conditions

With the increasing proportion of natural gas consumption in the energy market, in order to meet the demand for seasonal peak regulation and emergency gas supply, it is urgent to research and develop the underground natural gas storage (UNGS). Different from the conventional oil and gas fields, the UNGS pipeline network needs to consider the boundary constraints under both injection and production conditions. Therefore, considering the characteristics of injection and production technology, this paper aims to constructs a Multiple Condition Hybrid model (MCH model) for optimizing the design parameters of UNGS pipeline network. This paper proposes a Hybrid Genetic Algorithm (HGA) for solving the MCH model of pipeline network design. In the solution of Case 1, HGA has a 10%–13% lower investment cost than GA while shortening the GA iterations by 50%–70%. Case 2 is revealed that the MCH model can be optimized to obtain lower pipeline network costs under the boundary of injection and production conditions. Finally, HGA is used to optimize the design parameters of the MCH model for the field example Case 3, and the pipeline network parameters are obtained that are about 17% lower than the field costs.

Rarefied Air: Drilling for Helium in North America

Helium is one of the most abundant in advanced medical technologies such as MRIs, and in cryogenics, aerospace applications, and microchip manufacturing. It is also used to fill party balloons. It’s essential, expensive, and supplies are running low. Helium is about 100 million times more abundant in one place—but that place is on the moon. While trace amounts can even be found in the very air we breathe, the gas is difficult to find in commercial quantities, and those quantities are usually found as a byproduct of natural gas discoveries. Historically, about 40% of the US supply of helium came from the Federal Helium Reserve, a US Bureau of Land Management (BLM)-operated storage reservoir, enrichment plant, and pipeline system near Amarillo, Texas. The reserve was set up in 1960 as a strategic repository so that BLM could supply crude helium to private helium refining companies, which in turn refined it and marketed it to consumers. In the mid-1990s, Congress passed a bill to sell off a large part of the reserve’s supply to help pay off the facility’s debt, and effectively set in motion the federal government’s exit from the helium business. In 2013, BLM said it would begin auctioning off an increased percentage of the reserve annually as part of the bill. Last year, BLM announced the closure of the reserve. At the time of the announcement, BLM Deputy Director for Policy and Programs William Perry Pendley said “now it is time for the US government to remove itself from the helium business and allow the private sector to further develop this industry to meet the supply needs of the United States, creating a sustainable economic model and jobs for Americans.” BLM held its final crude helium auction in 2019, with the price rising 135%, from $119/Mcf a year earlier to $280/Mcf. Market pricing for helium is difficult to know. It is not a traded commodity, and pricing is normally based on long-term, confidential contracts. It’s a niche market that suffers from a lack of detailed analysis due in large part to the availability of its closely held data. The helium industry shares many aspects of the oil and gas business. Commercial deposits are found via geological survey; then, once identified, drilling begins. Outside of the search and discovery, helium can also be a useful tool for those in the oil business. It can be used for leak detection and in specialized welding due to its inert properties and high heat transfer. Additionally, as the oil field moves more toward digitalization, storage of big data will need helium for the construction of storage drives and to keep server farms cool. Swapping Hydrocarbons for Helium As scientific developments advance, the need for helium increases—a notion not lost on Canada-based Avanti Energy. The company’s CEO Chris Bakker has more than 2 decades of experience in oil and gas, most recently working as a commercial negotiator with Encana/Ovintiv for major facilities and pipelines in the Montney gas play. Today, he and his team are looking for commercial helium deposits in southern Alberta and northern Montana.

Error-Correcting Codes for Noisy Duplication Channels

Because of its high data density and longevity, DNA is emerging as a promising candidate for satisfying increasing data storage needs. Compared to conventional storage media, however, data stored in DNA is subject to a wider range of errors resulting from various processes involved in the data storage pipeline. In this article, we consider correcting duplication errors for both exact and noisy tandem duplications of a given length k. An exact duplication inserts a copy of a substring of length k of the sequence immediately after that substring, e.g., ACGT → ACGACGT, where k=3, while a noisy duplication inserts a copy suffering from substitution noise, e.g., ACGT → ACGA TGT. Specifically, we design codes that can correct any number of exact duplication and one noisy duplication errors, where in the noisy duplication case the copy is at Hamming distance 1 from the original. Our constructions rely upon recovering the duplication root of the stored codeword. We characterize the ways in which duplication errors manifest in the root of affected sequences and design efficient codes for correcting these error patterns. We show that the proposed construction is asymptotically optimal, in the sense that it has the same asymptotic rate as optimal codes correcting exact duplications only.

Coordinated Planning of Electricity/gas/storage Distribution Network Based on LSTM and Demand Response

This paper presents a collaborative planning method of an electricity-gas-storage regional integrated energy system based on LSTM neural network and demand response. First, the LSTM Neural network is used for load forecasting, and the energy hub structure of the electric gas storage system is established. Then, the mathematical models of power storage, gas storage, electric network topology, gas network topology, and P2G are established to minimize the expansion cost of the electricity-gas-storage system, and the collaborative planning of energy storage, power lines, and natural gas pipelines is proposed based on the existing electric gas coupling integrated energy system. The original model which is difficult to solve is transformed into a mixed-integer linear programming model by introducing auxiliary variables, and the CPLEX solver is called to solve it. Finally, the economic advantages of collaborative planning of electricity-gas-storage system are verified by an example, and the connection of power storage and gas storage can reduce system pressure and optimize equipment selection.

Failure pressure analysis of hydrogen storage pipeline under low temperature and high pressure

Low temperature and high pressure line pipes are widely used in hydrogen storage, air separation plant, liquefied natural gas (LNG) transportation etc. The material properties of pipes at low temperature are different from those at room temperature. If the medium in the pipe is corrosive, it will cause the pipe wall thickness to decrease. However, the failure pressure of the corroded hydrogen storage pipeline at extremely low temperature is lacking of adequate understanding. In this paper, we provided a novel failure pressure equation of the mild steel line pipe with corrosion defects at extremely low temperature. Firstly, a mechanical model of the line pipe with corrosion defects is established. And then, an analytical solution of the mechanical model is obtained based on elastic theory. Next, a failure pressure equation of the corroded hydrogen storage pipeline at extremely low temperature is developed. In the end, the accuracy of the failure pressure equation is verified by comparing with finite element method (FEM). The results suggest that the calculated value of the failure pressure equation is consistent with that of FEM. This paper provides a theoretical basis for the safety assessment of low temperature hydrogen storage pipeline. The new equation presented in this paper can provide useful guidance for the design of low temperature and high pressure pipelines.

Technical Note: Characterization of Corrosion Films Formed on Austenitic Stainless Steel in Supercritical CO2 Containing H2O and O2

Future technologies require structural alloys resistant to corrosion in supercritical CO2 (sCO2) fluids containing impurities such as H2O and O2. Traditional pipeline steels are potentially unsuitable for these environments and more corrosion resistant alloys such as stainless steels might be required. Little is known about the corrosion products formed on, and hence the processes which control corrosion of, stainless steels in impure sCO2 environments. In this study, austenitic stainless steel 347H (UNS S34709) was exposed to sCO2 containing H2O and O2 at 8 MPa and 50°C or 250°C, and separately to the aqueous phase in equilibrium with the sCO2 at 50°C, to simulate conditions expected in sCO2-based power cycles and carbon capture and storage pipelines. Only thin (<20 nm) surface films formed after 500 h resulting in small mass changes and corrosion rates <10−4 mm/y, suggesting the material resists significant degradation in these environments. X-ray photoelectron spectroscopy and transmission electron microscopy were used to characterize the corrosion films in detail. Exposure to the aqueous phase resulted in a thin (<5 nm) Cr-oxide and/or -hydroxide passive film, while exposure to sCO2 phases resulted in a multilayer Fe-rich oxide structure characteristic of a gas-phase oxidation process.

Effects of SO2 contamination on rising CO2 drops under high pressure

Although the flow dynamics of pure liquid drops in other liquids has been well researched, little attention has been paid to the impacts of impurities. Hence, most of research is not directly applicable to the real world. To address this gap, we conducted numerical experiments simulating the rise of pure and contaminated drops. It was selected to study liquid CO2 drops contaminated with SO2 under high pressure because such mixtures mimic potential scenarios in which drops may leak from carbon capture and storage (CCS) facilities or pipelines. First, numerical simulation experiments were performed to validate our method by comparing our results with previous research on pure drops. Second, the validated numerical approach was applied to simulations of contaminated drops to investigate how contaminants affect rising drops. The results show that the SO2 contamination caused changes in deformation, breakup phenomena, rising velocities, surrounding flow fields and drag coefficients. Most importantly, the contamination resulted in the formation of smaller “child drops”; such breakup is not observed in pure CO2 drops. The formation of child drops in turn affects the streamlines, patterns and areas of wakes behind the contaminated drops. The addition of contaminants also enhances the dissolution rate, which is affected by the contaminant concentration and by the flow dynamics of the rising drop. Our results would improve understanding the rise of impure CO2 drops, such as drops potentially leaked by future CCS operations.

Power profiling of multimedia sensor node with name-based segment streaming

Multimedia streaming from miniaturized sensors is attractive for a wide range of web-based applications, including surveillance and Internet of Things (IoT) applications. This paper profiles the power consumption in a wireless video sensor node. We compare the power consumption of video streaming frameworks based on a manifest file, such as the Hypertext Transfer Protocol (HTTP) Live Streaming (HLS), with a Wireless Video Sensor Network Platform compatible Dynamic Adaptive Streaming over HTTP (WVSNP-DASH) framework. The WVSNP-DASH framework is based on independently playable video segments that convey the metadata required for playback in their names (and do not require a manifest file). The power consumption components of the video capture and storage pipeline are evaluated. The presented extensive power profiling measurements provide real-world empirical data on architectural design decisions for multimedia sensor nodes suitable for IoT applications. Our measurement results indicate that the name-based WVSNP-DASH framework is well suited for flexible low-power web-based video streaming from miniaturized sensors.

Considerations in the Development of Flexible CCS Networks

This paper discusses considerations for the design of flexibly operated Carbon Capture and Storage (CCS) pipeline networks and is based on the findings of the Flexible CCS Network Development project (FleCCSnet), funded as part of the UK CCS Research Centre. The project considered the impact of flexibility across the whole CCS chain, as well as studying the interfaces between each element of the system; e.g. at the entry to the pipeline system from the capture plant and at the exit from the pipeline to the storage site. The factors identified are intended to allow CCS network designers to determine the degree of flexibility in the system; allowing them to react effectively to short, medium and long term variations in the flow of CO2 from capture plants and the constraints imposed on the system by CO2 injection and storage.The work of the project is reviewed in this paper which explores the flexibility of power plants operating with post combustion capture systems; quantifies the available time to store (line pack) CO2 in the pipeline as a function of pipeline size, the inlet mass flow rate and operating pressure; and explores the influence that uncertainty in injection and storage parameters have on the design of the pipeline. In addition, parameters influencing short and longer term network designs are discussed in terms of varying flow rates. Two practitioner workshops [1,2] contributed to the direction of the project. The first workshop identified and confirmed key questions to be considered in order to understand the most likely impacts of variability in both the CO2 sources and CO2 sinks on CO2 transport system design and operation. The second workshop focused on transient issues in the pipeline and storage site.Although the case studies in the work are UK based, this work is applicable to other situations where large and small sources of CO2 are expected to be feeding into a CCS transportation system. The work is expected to inform a broad range of stakeholders and allow network designers to anticipate potential problems associated with the operation of a CCS network. For an effective design of CCS infrastructure, all of the factors that will have a substantial impact on CO2 flow will have to be analysed at an early stage to prevent possible bottle necks in the whole chain.

Flow measurement of wet CO2 using an averaging pitot tube and coriolis mass flowmeters

The flow measurement of wet-gas is an active field with extensive research background that remains a modern-day challenge. The implication of wet-gas flow conditions is no different in Carbon Capture and Storage (CCS) pipelines. The associated complex flow regime with wet-gas flow makes it difficult to accurately meter the flow rate of the gas phase. Some conventional single-phase flowmeters like the Coriolis, Orifice plate, Ultrasonic, V-Cone, Venturi and Vortex have been tested for this application, usually accompanied with special recommendations. Often, a correlation equation valid within a certain range of specific conditions is required to correct the response of the flowmeter. This paper presents investigations into the suitability and performance of one of the most advanced averaging pitot tubes for the flow measurement of wet CO2 gas. The averaging pitot tube with flow conditioning wing geometry (APT-FCW) was studied and experimentally assessed in earlier work for the flow measurement of pure and dry CO2 within an error of ±1%. Under wet-gas conditions, however, the APT-FCW sensor is found to give an error of up to ±25% and within ±1.5% after appropriate correcting solutions are applied for a liquid fraction of up to 20%.

Statistics and Analysis of Corrosion Damage of Fuel Storage Pipelines and Vertical Tanks

Statistics and Analysis of Corrosion Damage of Fuel Storage Pipelines and Vertical Tanks

Carbon Capture and Storage (CCS) pipeline operating temperature effects on UK soils: The first empirical data

This paper presents the first empirical data of soil temperature and soil moisture profiles with depth in the context of a buried Carbon Capture and Storage transportation pipeline operating at higher than ambient soil temperatures. In an experimental approach, soil temperature responses are non-linear and are raised and restricted to within 45cm of the subsurface heat source (hypothetical pipeline). A surface heat source is included to investigate interactions of natural seasonal surface heating of soils with subsurface heat. There is no interaction between subsurface and surface heat sources in the experimental system. Soil moisture profiles vary with soil type, with overall soil moisture losses of >10% over experimental time courses. Modelled soil temperature profiles show that the ability of soils to buffer thermal movement from depths up to 1.2m from the surface is currently inadequately represented. Measurements provide the first elementary data of soil temperature changes resulting from a subsurface heat source for more accurate modelling of soil/pipeline interactions.