13 results about "Systems evolution" patented technology

The invention discloses an evolution simulation method and system for uranium dioxide heavy structure behaviors, and relates to the technical field of crystal evolution, and the method comprises the following steps: in a current time step, solving a pore-containing polycrystalline system evolution phase field model to obtain a vacancy concentration field variable and a grain orientation sequence parameter of the current time step; correcting the pore migration speed through the temperature distribution of the next time step; correcting grain orientation sequence parameters of the different air holes based on grain orientation and generation positions of columnar crystals generated by the different air holes; iteration is carried out on the next time step based on the corrected pore migration speed and grain orientation sequence parameters; and carrying out visualization processing on the vacancy concentration field variable and the grain orientation sequence parameter after iteration is finished to obtain the morphology evolution process of the pores and the grains in the uranium dioxide heavy structure process. According to the invention, a columnar crystal generation mechanism in a uranium dioxide heavy structure process is reflected, and simulation of an evolution process of generating columnar crystals with different orientations by migration of one or more pores is realized.

The invention provides an urban human-water system complex mutual feedback relation identification method based on a system evolution model, and the method comprehensively considers the factors of population change, water resource utilization, water pollution control, urban economic development and the like of a research area. Comprising the following steps: S1, analyzing the evolution characteristics of three subsystems of people, water and city in a research area, and evaluating the coupling coordination degree of the three subsystems; s2, gathering related data, carding causal relationships among the interiors of the three subsystems, constructing a quantification equation, and constructing a mutual feedback evolution model of the urban human-water system by adopting a system dynamics method; and S3, verifying the simulation effect of the model through visual inspection and historical inspection. According to the method, the complex mutual feedback relation among human, water and city multi-elements can be clarified, the human, water and city multi-element mutual feedback evolution process is simulated, finally, a universal model framework is established, the framework can be applied to human, water and city coupling systems in different urban regions, and technical support is provided for achieving coordinated development of the urban economic society and the water resource environment.

The application discloses a kind of Yellow River Basin cascade reservoir group system sustainable development regulation methods, comprising: the watershed system is divided into water and sediment, ecological and social subsystem, obtains multidimensional parameter data and identifies the order state flow variable of driving system evolution;The same vibration degree of order state flow variable is calculated, and the same vibration degree represents the coordination level of variable evolution;Overall harmonic contractility of system is calculated based on the same vibration degree;Select water and sediment regulation factor, construct the quantitative regulation model including water and sediment regulation factor, the same vibration degree of order state flow variable and the mapping relationship of system harmonic contractility;The target harmonic contractility interval of system is set, and based on quantitative regulation model, the water and sediment regulation factor regulation threshold required for realizing the target is calculated reversely.The application introduces evolution coordination analysis and reverse regulation mechanism, solves the problems that traditional method is difficult to quantify time sequence synchronism and cannot backstep regulation boundary, realizes the target-oriented accurate regulation of watershed system.

Examples related to a system evolution architecture for optimizing a media content editing system are provided. One aspect includes a method of optimizing a media content editing architecture, the method comprising: editing media content using a large language model and a back-end tool service, the back-end tool service comprising a cue pool and a plurality of application programming interfaces corresponding to a plurality of editing tools; publishing the edited media content; storing contextual information related to editing of the media content; and optimizing the media content editing architecture using the stored contextual information.

The present invention proposes a method for power system evolution deduction based on hierarchical collaborative simulation, which belongs to the field of new power system long-term planning. The method includes the following steps: constructing the power system evolution boundary, simulating the power system vision design, and embedding the power system source-grid-load-storage collaborative planning simulation with short-term operation simulation to form the current stage power grid planning scheme and record the evolution stage scheme and make evolution termination judgment to connect each stage in series to form a long-term evolution result. The present invention summarizes the evolution process into three levels of simulation: long-term, medium-term and short-term according to the characteristics of different links of the power system. Through modular modeling and solution of each layer of simulation, multi-factor and multi-time scale coupling simulation is realized, and the modeling complexity and accuracy are taken into account, so it can be used for large-scale system evolution deduction; at the same time, modular modeling and solution support the customized assembly of the main link models and solution methods of the evolution system while maintaining good openness, significantly improving the scalability and adaptability of the evolution system.

This invention discloses a robot navigation method suitable for large sparse environments, comprising the following steps: Step 1, establishing a system evolution equation based on the robot's state vector and kinematic equations, incorporating an environmental sparsity factor into the system evolution equations, and then introducing trajectory tracking weights and obstacle avoidance weights to construct a dynamic system model; Step 2, determining whether the dynamic system model is in a critical state between stability and chaos by solving the Jacobian matrix and Lyapunov exponent of the dynamic system model. When the maximum Lyapunov exponent is approximately equal to 0, the critical stability condition is reached; Step 3, based on the critical state, designing a path evaluation function to screen stable path points, and dynamically adjusting the obstacle avoidance weights through bifurcation parameter adjustment control equations to achieve adaptive switching between ordered tracking and chaotic obstacle avoidance, thus completing robot navigation in large sparse environments. This invention can ensure that robots can efficiently and stably complete navigation in large sparse environments.

This invention discloses a collaborative optimization design method for bearing systems based on TRIZ theory, belonging to the field of mechanical design and innovation methods. First, based on the optimization requirements of the bearing system performance, this invention establishes a three-level functional model of supersystem-system-subsystem and identifies key problem clusters. The functional model includes at least one of the following: useful functions, harmful functions, insufficient functions, and excessive functions. Then, based on the three-level functional model, contradiction solutions and resource analysis are performed at the component level, system level, and supersystem level to obtain contradiction solutions. Subsequently, a matter-field model is constructed and solved, and the TRIZ evolutionary law is applied to guide system reconstruction to obtain a system evolution scheme. Finally, the contradiction solutions and the system evolution scheme are cross-integrated and their feasibility is evaluated to generate an innovative conceptual design scheme for the bearing system. This invention effectively solves the problems of existing technologies being limited to single problems and isolated components.

The embodiment of the invention discloses a system evolution capability verification method and system based on breakpoint regression and entropy analysis, and the method comprises the steps: constructing a system evolution evaluation system comprising a plurality of evaluation dimensions; a stable closed environment is provided through an environment control module, and operation data of a target system in the closed environment is collected through a multi-mode sensor network; adopting a preset breakpoint detection algorithm, setting a significance level index, analyzing the operation data, identifying a state sudden change point of the target system, and calculating a breakpoint regression design score; based on an information entropy principle, calculating a structure entropy, a function entropy and an energy entropy; calculating an evolutionary ability index according to the structural entropy, the functional entropy, the energy entropy and the breakpoint regression design score; and judging whether the target system has the autonomous evolution ability or not according to the evolution ability index. According to the invention, precise control and high-precision multi-dimensional data acquisition of the system environment are realized, and quantitative verification of the system evolution capability is realized.

The present invention discloses a method, device and medium for constructing an evolutionary model of an autonomous transportation system. The method includes: determining system elements and element attributes according to the architecture of the autonomous transportation system; determining the association relationships of the system elements according to the element attributes; building a multi-layer complex network structure according to the association relationships and inputting a configuration package into the multi-layer complex network structure; establishing an evolutionary model of the complex network of the autonomous transportation system facing the target layer according to the multi-layer complex network structure and in combination with a first preset standard, and determining the attribute of the evolutionary state value of the evolutionary model; determining the initial state value and attribute value of the evolutionary model according to a second preset standard, and driving the evolutionary model to evolve according to the initial state value and attribute value; outputting the evolutionary data of the evolutionary model and performing feature analysis according to the evolutionary data. The beneficial effect of the present invention is that it can scientifically describe and predict the evolutionary characteristics and development laws of the autonomous transportation system, which is beneficial to the sustainable development of the transportation system.

This invention presents a unified framework for addressing complex, multi-domain challenges through adaptive design optimization, equation discovery, and hypothesis generation. Central to the framework is the Mathematical Sphere Framework (MSF), which employs advanced machine learning and hybrid computing to interrelate equation families across fields such as CFD, FEM, CAD, and PLM. MSF enables cross-domain optimization with transparent, physics-based representations, fostering continuous insight generation and system evolution. A neural-assisted system refines equations from experimental and real-world data, advancing theoretical models and design exploration. Hybrid computing combines classical preprocessing with quantum optimization to enhance computational efficiency. A digital twin provides real-time simulation and predictive analysis, while lifecycle adaptability dynamically optimizes parameters across product stages. By improving efficiency, scalability, and interoperability, this invention transforms engineering workflows, supports innovation, and fosters cross-industry applications, including aerospace, energy, and manufacturing, driving progress in an ever-evolving landscape.

The invention discloses a power distribution network in-disaster dynamic reconstruction method based on a look-ahead-rehearsal algorithm, and belongs to the technical field of power distribution network reconstruction. The invention discloses an in-disaster dynamic reconstruction method for a power distribution network based on a look-ahead-preview algorithm. The method comprises the following steps: inputting an initial operation state of the power distribution network; acquiring a system state # imgabs0 # at the current moment; generating a set # imgabs1 # of all feasible actions at the current moment; performing an evaluation process on each action # imgabs2 #, constructing a future disaster scene by using a Monte Carlo method, simulating a system evolution process in combination with a basic strategy, and evaluating the expected cost of the action # imgabs3 # in the whole decision period; the action with the minimum expected cost is selected as the optimal action at the current moment to be executed, and the system state # imgabs4 # is updated; and S2, updating the time step, if the current time step # imgabs5 #, returning to S2 to continue decision making, otherwise, stopping algorithm execution. According to the reconstruction method, the current decision is optimized, the influence of the current decision on the future is considered, the efficient and rapid in-disaster dynamic reconstruction decision is realized, and the reliability and toughness of the power distribution network are improved.

A memory-governed supervisory and evolutionary system is disclosed in which authority to influence system evolution is constitutionally constrained through adjudicated memory admission. Information from external sources and internally generated outputs is recorded as candidate memory resources within a structured memory architecture and rendered ineffective prior to adjudication by a write barrier. Admission occurs under a governance framework defining admissible evolution ranges, and system evolution arises exclusively from admitted structured memory resources. Supervisory outputs generated from admitted memory resources are expressive and non-executable, while execution and enforcement actions occur exclusively outside the system boundary. The disclosed architecture structurally separates information, authority, and execution, preventing delegation of authority to computation, intelligence, or external execution and enabling governed system evolution across asynchronous and heterogeneous environments.

This invention discloses a structurally variable coupled chaotic system and its applications, belonging to the field of information security technology. The coupled chaotic system is formed by the coupling of multiple discrete chaotic systems. During system evolution, the coupling structure between different subsystems is dynamically changed in real time by manipulating the coupling matrix. The coupled system exhibits complex dynamic behavior and high nonlinearity, and the dynamic changes in structure cause continuous abrupt changes in the system's dynamics, resulting in non-stationary chaotic sequences. This system is resistant to attacks from statistical analysis, algebraic analysis, and other methods, exhibiting extremely high security. Furthermore, this system is applicable to various chaotic systems and complex chaotic networks of arbitrary scale. It can also generate complex dynamics based on simple discrete chaotic systems. Under the same complexity and security requirements, controlling structural changes results in lower overhead. It can be used to design high-performance chaotic cryptographic systems and as a component in network security applications.