Storage Engine Research Articles

Recent Advances in Liquid Metals for Rechargeable Batteries

AbstractLiquid metals (LMs) with their unique properties are considered for a range of applications such as energy storage, catalysis, electronics, and biomedical engineering. Recently, the introduction of LMs into rechargeable batteries has not only proven to improve overall performance but also overcome commonly known challenges like low energy density, material degradation, interface failure, and poor system integrity. Specifically, room‐temperature LMs such as gallium (Ga), Ga‐based alloys (GBAs), and metallic mercury (Hg) are promising candidates in rechargeable batteries due to their low viscosity, high electrical and thermal conductivity, excellent deformability, superior electrochemical properties, and self‐healing capability. Herein, a review of recent advances in LMs for rechargeable batteries, starting with a brief introduction to LMs fundamentals and their properties is presented. Then, an extensive literature review is carried out to summarize the LMs’ advances in addressing existing challenges of lithium‐ion, lithium‐metal, lithium–sulfur, and other rechargeable batteries. The current state of the art and future perspective are also put forward. It is believed that highlighting potential developments pertaining to LMs can fascinate researchers in exploring them for future rechargeable batteries.

On the Performance Intricacies of Persistent Memory Aware Storage Engines

As key components of DBMSs, various storage engines and index structures have been proposed based on incorrect assumptions before PMem hardware is publicly available. Recent studies reveal that there is a significant performance gap in evaluating index structures on real PMem platforms as compared to DRAM-based emulators. However, a comprehensive evaluation for those PMem-aware database storage engines on real PMem hardware is still missing. Meanwhile, dynamic memory management is more important on PMem systems because PMem is slower than DRAM and unfriendly to random small-writes, and ensuring crash-consistency for the metadata of PMem allocators introduces extra overhead. Therefore, it is essential to understand the performance intricacies of PMem-aware database storage engines from the perspective of PMem allocators. This paper presents a systematic evaluation of three PMem-aware database storage engines using representative workloads and a unified benchmarking framework that is integrated with four PMem allocators. Besides the commonly used metrics, the impact of different hardware configurations (such as NUMA and eADR) on performance is also considered. Through in-depth analysis, we reveal caveats and pitfalls on using or designing PMem-aware storage engines and important insights that can serve as guidelines for future development of PMem allocators and other related components.

Rainwater Storage Engineering based on Water-Sensitive Urban Design in Lapangan Pancasila, Semarang City

Lapangan Pancasila is a public open space that located in Jln. Seroja Dalam III no. 9 Semarang City. Flooding is often occurs at Lapangan Pancasila in rainy season. Floods in Semarang City are caused by the occurrence of land subsidence and water catchment area decreases. Rainwater harvesting system with water sensitive urban design(WSUD) basic, is one of plenty solution that can be applied to reduces flooding at Lapangan Pancasila. The research was conducted using a descriptive methodology which refers to the spatial and ecological approach. A spatial approach is used to determine the physical condition of the site, while an ecological approach is used to determine the components required for engineering rainwater storage. Based on the calculations that have been carried out, the discharge from the calculation of the planned rainfall is 0.003886 m3/s. Rainwater collection engineering at Lapangan Pancasila was built as a complex system that combines various components of rainwater treatment such as rainwater catchment areas, macro water filtration tanks, sand filter tanks to filter mud and purify water, clean water reservoirs, sprinkle landscape irrigation systems, and infiltration wells.

Investigation of the influence of model control parameters on fracture characteristics of GPU parallel FDEM

Surrounding rock mass fracture characteristics play a significant role in the understanding of the CO2 geological storage and utilization (CGSU) engineering practices in abandoned mines. The combined finite discrete element method (FDEM) shows advantages in simulating fracture and fragmentation of rock-like materials, however, many computational parameters and a lack of basis for accurate values affect the simulation results. For systematic explorations of the influence of the effect of model parameters with different time steps, this study conducted different loading rate specimen tests and unloading rate tests both in laboratory-scale tests and field-scale based on the CUDA-based GPU parallel FDEM program. In laboratory-scale uniaxial compressive strength (UCS) tests, a smaller loading rate ensures a quasi-static loading process and should be below 0.1 ms−1 for simulation. Then, continuous optimization and improvement of the GPU parallel FDEM in tunnel excavation were proposed, and the model parameters reflect the continuous improvement of the simulation results. In the process, the tunnel excavation simulation method with the reduction rate of the opening zone’s Young's modulus in the excavation was performed to investigate the unloading mode and rate by continuing to optimize the GPU parallel FDEM program and model parameters. Besides, the main factor in fracture mode and failure mechanism of the surrounding rock mass also was calibrated. The results indicate that the system kinetic energy of the model is maintained at a small level with the reasonable unloading mode and critical threshold set at a small value, the damping parameters, dissipation mechanism, and excavation fractures are clearer and reasonable, and the computational cost is significantly reduced with GPU parallel FDEM.

Preface

The 2023 2nd International Conference on New Energy, Energy Storage and Power Engineering (NESP 2023), held from April 21st to 23rd, 2023 in Kaifeng, China (virtual event), is a premier academic conference on new energy, energy storage and power engineering for research individuals and groups working on related fields. It allows researchers to share their experiences with other groups from all over the world by presenting scientific work and potential innovations in this research area and also in the social events promoting informal get togethers.The works cover a broad range of fields, including Electrochemical Energy Storage Device, Lithium Sulfur Batteries, Energy Storage Material, Power Transmission, Power Quality Protection and Electromagnetic Compatibility, etc. Also, the Conference is intended to give students and research groups the opportunity to learn more about new energy, energy storage and power engineering as an important tool in their applications and development.The Conference is designed to showcase cutting-edge research and accomplishments, and to enrich the educational and industrial experience in this field. It also represents a unique opportunity for all the participants to meet colleagues and friends, exchanging ideas, and learning about new developments, while working to advance the understanding of the knowledge base that we will collectively draw upon in the years ahead to meet future challenges. Participants will attend presentations by scholars representing both institutes and academia.The NESP 2023 Proceedings include about 110 papers selected via a peer review process. The Conference Program features keynote speeches by eight world-leading scholars and many sessions for regular paper oral presentations, attracting around 150 participants. Among them, Professor Pierluigi Siano from University of Salerno, Italy gave a speech. His research activities are centered on demand response, on the integration of distributed energy resources in smart grids and on planning and management of power systems. He has co-authored more than 450 papers including more than 200 international journal papers that received more than 7600 citations with an H-index equal to 44.In making this Conference possible, we want to acknowledge our deep appreciation for the support of Murdoch University, Australia and Universiti Tunku Abdul Rahman, Malaysia. And we would like to extend an enthusiastic round of thanks to all our conference authors for their excellent contributions; to all the session Chairs for their effort and enthusiasm; and to all the Technical Program Committee members and referees for their time and expertise in the paper reviewing process. Particular acknowledgement to the staff of Journal of Physics: Conference Series for their time and outstanding publishing work.The Committee of NESP 2023List of Committee Member are available in this pdf.

First-Principles Investigation of Size Effects on Cohesive Energies of Transition-Metal Nanoclusters.

The cohesive energy of transition-metal nanoparticles is crucial to understanding their stability and fundamental properties, which are essential for developing new technologies and applications in fields such as catalysis, electronics, energy storage, and biomedical engineering. In this study, we systematically investigate the size-dependent cohesive energies of all the 3d, 4d, and 5d transition-metal nanoclusters (small nanoparticles) based on a plane-wave-based method within general gradient approximation using first-principles density functional theory calculations. Our results show that the cohesive energies of nanoclusters decrease with decreasing size due to the increased surface-to-volume ratio and quantum confinement effects. A comparison of nanoclusters with different geometries reveals that the cohesive energy decreases as the number of nanocluster layers decreases. Notably, monolayer nanoclusters exhibit the lowest cohesive energies. We also find that the size-dependent cohesive energy trends are different for different transition metals, with some metals exhibiting stronger size effects than others. Our findings provide insights into the fundamental properties of transition-metal nanoclusters and have potential implications for their applications in various fields, such as catalysis, electronics, and biomedical engineering.

Enabling Timely and Persistent Deletion in LSM-Engines

Data-intensive applications have fueled the evolution of log-structured merge (LSM) based key-value engines that employ the out-of-place paradigm to support high ingestion rates with low read/write interference. These benefits, however, come at the cost of treating deletes as second-class citizens . A delete operation inserts a tombstone that invalidates older instances of the deleted key. State-of-the-art LSM-engines do not provide guarantees as to how fast a tombstone will propagate to persist the deletion . Further, LSM-engines only support deletion on the sort key. To delete on another attribute (e.g., timestamp), the entire tree is read and re-written, leading to undesired latency spikes and increasing the overall operational cost of a database. Efficient and persistent deletion is key to support: (i) streaming systems operating on a window of data, (ii) privacy with latency guarantees on data deletion, and (iii) en masse cloud deployment of data systems. Further, we document that LSM-based key-value engines perform suboptimally in the presence of deletes in a workload. Tombstone-driven logical deletes, by design, are unable to purge the deleted entries in a timely manner, and retaining the invalidated entries perpetually affects the overall performance of LSM-engines in terms of space amplification, write amplification, and read performance. Moreover, the potentially unbounded latency for persistent deletes brings in critical privacy concerns in light of the data privacy protection regulations, such as the right to be forgotten in EU’s GDPR, the right to delete in California’s CCPA and CPRA, and deletion right in Virginia’s VCDPA. Toward this, we introduce the delete design space for LSM-trees and highlight the performance implications of the different classes of delete operations. To address these challenges, in this article, we build a new key-value storage engine, Lethe + , that uses a very small amount of additional metadata, a set of new delete-aware compaction policies, and a new physical data layout that weaves the sort and the delete key order. We show that Lethe + supports any user-defined threshold for the delete persistence latency offering higher read throughput (1.17× -1.4×) and lower space amplification (2.1× -9.8×), with a modest increase in write amplification (between 4% and 25%) that can be further amortized to less than 1%. In addition, Lethe + supports efficient range deletes on a secondary delete key by dropping entire data pages without sacrificing read performance or employing a costly full tree merge.

Combining Metabolic Engineering and Lipid Droplet Storage Engineering for Improved α-Bisabolene Production in Yarrowia Lipolytica.

Bisabolene is a bioactive sesquiterpene with a wide range of applications in food, cosmetics, medicine, and aviation fuels. Microbial production offers a green, efficient, and sustainable alternative. In this study, we focused on improving the titers of α-bisabolene in Yarrowia lipolytica by applying two strategies, (i) optimizing the metabolic flux of α-bisabolene biosynthetic pathway and (ii) sequestering α-bisabolene in lipid droplet, thus alleviating its inherent toxicity to host cells. We showed that overexpression of DGA1 and OLE1 to increase lipid content and unsaturated fatty acid levels was essential for boosting the α-bisabolene synthesis when supplemented with auxiliary carbon sources. The final engineered strain Po1gαB10 produced 1954.3 mg/L α-bisabolene from the waste cooking oil under shake flask fermentation, which was 96-fold higher than the control strain Po1gαB0. At the time of writing, our study represents the highest reported α-bisabolene titer in the engineered Y. lipolytica cell factory. This work describes novel strategies to improve the bioproduction of α-bisabolene that potentially may be applicable for other high-value terpene products.

Experimental investigation on mechanical behavior, energy evolution and gas permeability of anisotropic phyllite subjected to triaxial compression and cyclic loading

The bedding plane direction significantly affects the mechanical properties, deformation and gas permeability evolution of rock mass in gas storage engineering. In this paper, for phyllite, a series of triaxial compression with cyclic loading and gas permeability apparatus are conducted to investigate such directional effect. The peak stress, Young’s modulus, energy evolution, failure mode and gas permeability coefficient are analyzed. For triaxial compression test, with increasing inclination angles, the deformation parameters (E, E50, μ) and characteristic stress parameters (σcc, σci, σcd) both show a U-shape pattern. For triaxial cyclic loading test, the peak stress of specimen first decreases and then increases, i.e., the peak stresses at the inclination angles of 0°, 30°, 45°, 60° and 90° are 118.18, 84.35, 64.18, 42.54 and 84.57 MPa, respectively. The energy evolutions of specimens at different inclination angles are similar, but increase with increasing cyclic number. i.e., when β=60°, with the cycle number increasing from 1 to 3, the elastic strain energy, the dissipated strain energy and the total strain energy increase by 343.55%, 175.08%, and 259.87%, respectively. In addition, the failure mode of phyllite specimens is analyzed and summarized as three distinct types, i.e., tensile-shear failure, shear-sliding failure and split-shear failure. The relationships between the initial gas permeability and confining pressure, deviatoric stress show positive correlations. The failure of layered phyllite is most likely to occur at a bedding plane inclination angle of 45° to 60°.

Disaggregating RocksDB: A Production Experience

As in the general industry, there is a trend in Meta's data centers to migrate data from locally attached SSDs to cloud storage. We extended RocksDB [26], a widely used open-source storage engine designed and built for local SSDs, to leverage disaggregated storage. RocksDB's design, such as its data and log files' access patterns, makes an append-only distributed file system a desirable underlying storage. At Meta, we built disaggregated RocksDB using Tectonic File System [35], which so far had mainly been used for our data warehouse and blob storage stacks. We identified that metadata overhead and tail latencies were Tectonic's major performance gaps and addressed them accordingly. We improved the reliability, performance and other requirements with both general and customized optimizations to the core engine in RocksDB. We also took the time to deeply understand the common challenges presented by applications running on RocksDB and implemented enhancements to address them. This architecture enabled RocksDB to adapt to a more distributed architecture for performance enhancements.

ForestTI: A Scalable Inverted-Index-Oriented Timeseries Management System with Flexible Memory Efficiency

Timeseries management systems play an important role in IoT and performance monitoring. As the data volume scales up, absorbing data memory efficiently with high throughput becomes a growing requirement for timeseries management systems. However, the designs of the existing systems, especially the in-memory data structures, suffer from two issues. First, they suffer from the trade-off between memory efficiency and performance. Second, they are not scalable because of lock contention where they cannot benefit from parallel insertion and querying. In this paper, we propose ForestTI, a scalable inverted-index-oriented timeseries management system where the balance point between memory efficiency and performance can be flexibly adjusted under the increasing memory pressure. First, we present a two-level inverted index, which is scalable with optimistic lock coupling, and its internal structure can be gradually converted to more memory efficient representations. Second, we propose a two-level pointer swizzling mechanism to actively swap out the cold posting lists and in-memory timeseries objects as the number of timeseries increases. Finally, we further optimize the on-disk data structures (i.e. write-ahead logs and LSM-tree) to adapt to the high insertion throughput from the in-memory components. We prototype ForestTI with C++ from scratch, and compared to the storage engine of Prometheus, ForestTI achieves 1.79x higher insertion throughput, 52.1% lower query latency, and 56.9% lower memory occupation. We have released the open-source code of ForestTI for public access.

Technical Perspective for Skeena: Efficient and Consistent Cross-Engine Transactions

The paper proposes a solution to the problem of inadequate support for transactions in multi-engine database systems. Multi-engine database systems are databases that integrate new (fast) memory-optimized storage engines with (slow) traditional engines, allowing the application to use tables in both engines. Multi-engine database systems are in particular interesting for traditional database systems that are extended over time. By being able to store tables in slow and fast storage engines and executing transactions cross engines allows to reduce overall cost since less performance critical tables can be placed in slow (and thus cheaper) storage. As

An Efficient On-Chip Data Storage and Exchange Engine for Spaceborne SAR System

Advancements in remote sensing technology and very-large-scale integrated circuit (VLSI) have significantly augmented the real-time processing capabilities of spaceborne synthetic aperture radar (SAR), thereby enhancing terrestrial observational capacities. However, the inefficiency of voluminous data storage and transfer inherent in conventional methods has emerged as a technical hindrance, curtailing real-time processing within SAR imaging systems. To address the constraints of a limited storage bandwidth and inefficient data transfer, this study introduces a three-dimensional cross-mapping approach premised on the equal subdivision of sub-matrices utilizing dual-channel DDR3. This method considerably augments storage access bandwidth and achieves equilibrium in two-dimensional data access. Concurrently, an on-chip data transfer approach predicated on a superscalar pipeline buffer is proposed, mitigating pipeline resource wastage, augmenting spatial parallelism, and enhancing data transfer efficiency. Building upon these concepts, a hardware architecture is designed for the efficient storage and transfer of SAR imaging system data, based on the superscalar pipeline. Ultimately, a data storage and transfer engine featuring register addressing access, configurable granularity, and state monitoring functionalities is realized. A comprehensive imaging processing experiment is conducted via a “CPU + FPGA” heterogeneous SAR imaging system. The empirical results reveal that the storage access bandwidth of the proposed superscalar pipeline-based SAR imaging system’s data efficient storage and transfer engine can attain up to 16.6 GB/s in the range direction and 20.0 GB/s in the azimuth direction. These findings underscore that the storage exchange engine boasts superior storage access bandwidth and heightened data storage transfer efficiency. This considerable enhancement in the processing performance of the entire “CPU + FPGA” heterogeneous SAR imaging system renders it suitable for application within spaceborne SAR real-time processing systems.

MODELING OF GROUNDWATER LEVEL CHANGES DUE TO DEEP WELL EXTRACTION USING MODFLOW IN THE NORTH OF BANDAR LAMPUNG

The growth rate of urban areas in the north of Bandar Lampung has caused the extraction of groundwater resources through deep well pumping to increase. Therefore, it is necessary to study the impact of pumping to prevent groundwater depletion. This study performs numerical simulation modeling to identify the impact of deep well pumping on changes in groundwater levels in three sub-districts north of Bandar Lampung city. Modeling is done using MODFLOW-6 and ModelMuse as a graphical user interface (GUI). The simulation method uses steady-state and transient models with four stress periods in 2000, 2010, 2020, and 2030. A total of 30 data wells are used for model setup, and 15 of them as observation and validation points. The simulation results show that hydraulic head changes occur at depths of 10 m to more than 40 m. Drawdown and groundwater head changes are concentrated at deep well points with a radius of up to 1 km. The model also successfully identified a decrease in groundwater level to more than 8 m in the deepest well area DW1. Thus, it is necessary to take action that can overcome the impact of changes in groundwater level due to pumping from deep wells. Furthermore, groundwater storage engineering can be one solution by utilizing rainwater harvesting technology to recharge the groundwater aquifer system.

Spatio-Temporal Model of a Product–Sum Simulation on Stream Network Based on Hydrologic Distance

The modeling of spatio-temporal processes is crucial in many fields such as environmental science, hydrology, and water storage engineering. A basic concept of the spatio-temporal model is an auto-covariance function. The stream network model based on the Euclidean distance as the auto-covariance function for investigating river pollution will potentially face a serious accuracy problem, due to the material or water pollutant movement on the water only occurring within the river network and the distance travelled not following the path of the river network. The use of the hydrologic distance may overcome the problem because, statistically, the Euclidean distance-based auto-covariance function is not valid if it is a negative-definite. Therefore, this study develops a spatio-temporal model of the generalized product–sum based on the hydrologic distance with a positive-definite property. The proposed model is built and, subsequently, it is then verified mathematically to be positive-definite. Furthermore, the relationships between the hydrologic distance, the Euclidean distance, and spatial configurations are also investigated. The simulation study result shows the proposed spatio-temporal model is positive-definite for some semivariogram models. The relationships between spatial configurations in the stream network follow an exponential model.

Advances in CO2 utilization employing anisotropic nanomaterials as catalysts: a review.

Anisotropic nanomaterials are materials with structures and properties that vary depending on the direction in which they are measured. Unlike isotropic materials, which exhibit uniform physical properties in all directions, anisotropic materials have different mechanical, electrical, thermal, and optical properties in different directions. Examples of anisotropic nanomaterials include nanocubes, nanowires, nanorods, nanoprisms, nanostars, and so on. These materials have unique properties that make them useful in a variety of applications, such as electronics, energy storage, catalysis, and biomedical engineering. One of the key advantages of anisotropic nanomaterials is their high aspect ratio, which refers to the ratio of their length to their width, which can enhance their mechanical and electrical properties, making them suitable for use in nanocomposites and other nanoscale applications. However, the anisotropic nature of these materials also presents challenges in their synthesis and processing. For example, it can be difficult to align the nanostructures in a specific direction to impart modulation of a specific property. Despite these challenges, research into anisotropic nanomaterials continues to grow, and scientists are working to develop new synthesis methods and processing techniques to unlock their full potential. Utilization of carbon dioxide (CO2) as a renewable and sustainable source of carbon has been a topic of increasing interest due to its impact on reducing the level of greenhouse gas emissions. Anisotropic nanomaterials have been used to improve the efficiency of CO2 conversion into useful chemicals and fuels using a variety of processes such as photocatalysis, electrocatalysis, and thermocatalysis. More study is required to improve the usage of anisotropic nanomaterials for CO2 consumption and to scale up these technologies for industrial use. The unique properties of anisotropic nanomaterials, such as their high surface area, tunable morphology, and high activity, make them promising catalysts for CO2 utilization. This review article discusses briefly about various approaches towards the synthesis of anisotropic nanomaterials and their applications in CO2 utilization. The article also highlights the challenges and opportunities in this field and the future direction of research.

Current state of the coal ash handling problem in Russia and abroad, aspects of the coal ash applications in hydrogen economy

One of the global state tasks, contributing to the implementation of the goal of developing the energy sector of the Russian Federation and given in the Energy Strategy of the Russian Federation for the period until 2035, is to reduce the negative impact of the fuel and energy complex industries on the environment.In this regard, special attention is paid to the coal ash handling problem, which is intensified by tightening of the environmental legislation with the transition to the principles of the best available technologies, greening of the coal power, depletion of the capacity of the coal ash disposal sites, etc. Disposal of ash, slag, ash-and-slag mixtures, formed at combustion of coal, peat and shale, is one of the main problems of the modern solid-fuel thermal power plants in Russia, the number of which makes 172. The average age of the coal-fired TPPs is about 50 years that significantly affects the technical and environmental performance of the ash removal system of TPPs. At the Russian TPPs for the ash and slag conveying hydraulic ash removal systems are the most common, used in the vast majority of cases being technically outdated, uneconomical and ecologically not friendly.Annually 25 … 30 million tons of ash and slag are formed at the coal-fired power plants of the Russian Federation. Currently more than 1.5 billion tons of ash and slag are accumulated at the ash disposal sites of thermal power plants, and every year these figures are growing. About 2/3 of all ash and slag disposals are close to the design filling or are already overfilled. Elimination of objects of the accumulated environmental damage, representing ash disposals of the coal-fired power plants, is one of the conditions for Russia's transition to the standards of “green” economy. The problem of coal-fired power plants in terms of elimination of the accumulated environmental damage can be solved only by implementing the large-scale projects of integrated coal ash processing, obtaining required products.The article provides statistical data for the 2019 relating to the volumes of the coal ash generation and utilization in various countries of the world. An overview of the various applications of the coal combustion by-products, the main of which are ash and slag, in Russia, India, China, EU countries, etc. is presented. The article contains data on the applicability of the coal ash for various technologies of its use according to the Russian Ministry of Energy. A review of scientific and technical information sources on the prospects of using coal ash in hydrogen power engineering for hydrogen sorption and storage is given, as well as a review of traditional methods of hydrogen storage. Terminology in the field of coal ash handling found in scientific and technical information sources is considered, and a classification of coal combustion by-products in Russia and abroad is given. The main recommendations of the author, contributing to the increase in the use of coal ash in Russia, are given.

Investigation of ambient temperature effects on the characteristics of turbulent diffusion flames: An experimental approach

Pool fires, commonly associated with industrial accidents, have posed a significant threat to the safety of industrial processes. This is particularly relevant in environments where storage tanks, engine cabinets, and boiler rooms are typically maintained. The effects of ambient temperature on the flame characteristics of gaseous pool fires were explored through a series of experiments conducted in a temperature-controlled chamber, with temperatures ranging from 40 ℃ to − 20 ℃. A modified flame height correlation accounting for the temperature effect was proposed. These findings have potential implications for enhancing the reliability of industrial design and fire risk assessment in environments with varying temperature conditions.

What Modern NVMe Storage Can Do, and How to Exploit it: High-Performance I/O for High-Performance Storage Engines

NVMe SSDs based on flash are cheap and offer high throughput. Combining several of these devices into a single server enables 10 million I/O operations per second or more. Our experiments show that existing out-of-memory database systems and storage engines achieve only a fraction of this performance. In this work, we demonstrate that it is possible to close the performance gap between hardware and software through an I/O optimized storage engine design. In a heavy out-of-memory setting, where the dataset is 10 times larger than main memory, our system can achieve more than 1 million TPC-C transactions per second.

Upper bound analysis of active and passive mechanisms of intermediate rock wall between two adjacent pressurised cavities

The construction of adjacent cavities is important for deep oil storage and tunnel engineering. However, studies on the failure mechanisms of intermediate rock walls are scarce. Rock walls for underground cavities, such as oil reservoirs and tunnels built near concealed karst caves, are exposed to pressure variations. Because the magnitude of pressure imposed on the inner surface of two cavities varies, different kinematic mechanisms and failure extents of rock walls can be observed. To derive the analytical expressions of the failure surface for rock walls, limit analysis is conducted within the framework of the upper bound theorem. The active and passive failure modes of rock walls are defined based on the variation in the magnitude of pressure on both sides of the walls. Furthermore, two failure states of rock walls are summarised according to the relationship between the pressure difference and weight of rock walls. Moreover, based on the upper-bound solutions, thenon-linearoptimisations for critical pressure and thickness of rock walls are implemented by assuming that both cavities are cylindrical (rectangles in two dimensions). The results of the presented methods and numerical simulations indicate that the magnitude of pressure difference determines the failure modes and shape characteristics of rock walls. Evidently, the effects of internal pressures on the stability of rock walls must be intently considered in the design of two adjacent underground cavities filled with fluid.