An estimated gas leak flow rate can be determined using a teaching set of concentration profiles, a regression model implemented by a machine-learning subsystem, and a subset of attributes measured within an environment. The teaching set of concentration profiles can include gas flow rates associated with relevant attributes. The regression model can be transformed into a gas leak flow regression model via the machine-learning subsystem using the teaching set. The subset of attributes measured within the environment can be applied to the gas leak flow regression model to determine other attributes absent from the subset of attributes and an estimated gas flow rate for the environment. A gas leak attenuation action can be performed in response to the estimated gas flow rate.

System, methods, and other embodiments described herein relate to determining an improved electrode design of a battery. In one embodiment, a method includes computing one or more equivalent circuits as porous electrode transmission line models corresponding to one or more electrode designs. Individual circuits of the equivalent circuits define an arrangement of electrode elements having at least two geometric degrees of freedom. The electrode designs are defined according to battery specifications indicating at least a battery volume, and a separator thickness. The method includes determining attributes for the equivalent circuits according to the at least the two geometric degrees of freedom in which the equivalent circuits are defined. The method includes identifying a target design of the electrode designs associated with one of or more of the attributes satisfying a circuit threshold. The target design improves one or more of the attributes in relation to the battery.

Systems and methods for automated resource allocation during a computational simulation are described herein. An example method includes analyzing a set of simulation inputs to determine a first set of computing resources for performing a simulation, and starting the simulation with the first set of computing resources. The method also includes dynamically analyzing at least one attribute of the simulation to determine a second set of computing resources for performing the simulation, and performing the simulation with the second set of computing resources. The second set of computing resources is different than the first set of computing resources.

In some examples, a system for generating optimization constraints includes a memory device to store human-generated constraint and/or objective definitions that have been programmed in a general-purpose programming language by a human user, and a processor configured to generate labeled data for a plurality of solutions to an optimization problem using the stored constraint and/or objective definitions. The processor is also configured to generate a formal constraint and/or objective model from the labeled constraint and/or objective data, wherein the formal constraint and/or objective model comprises automatically generated constraint and/or objective definitions that are syntactically different from the human-generated constraint and/or objective definitions and syntactically correct for a specific optimization engine.

The present disclosure discloses a model-based architecture design method for an unmanned aerial vehicle (UAV) system, which aims to deal with challenges of changeable operational requirements, shortened design period, and decreased technical risks in a current UAS design process. A data-driven architecture development method is used. By establishing an architecture development framework of the UAS, a framework modeling process oriented to different viewpoints is designed, and modeling and simulation specifications based on SysML and Modelica are defined, such that design of the UAS starts from conception and confirmation of an operational concept. The method focuses on forward analysis and design of a system framework, and concept verification and metric closed-loop are carried out at an early stage of the design of the UAS by virtue of logic modeling and system simulation.

The present disclosure provides an edge and bottom water invasion simulation apparatus and method, a storage medium, and a product. A controller controls an inert gas to be injected into a first intermediate container, and stops the injection. The controller controls formation water to be injected into the first intermediate container, and stops the injection. The controller controls the first intermediate container to be communicated with a core holder, and adjusts a pressure of a back pressure valve, so that the formation water enters a core to simulate edge and bottom water invasion. In the present disclosure, by adding the inert gas and the formation water to the intermediate container, an infinite edge and bottom water with sufficient energy at an early stage of a water invasion and a limited edge and bottom water with lower energy at a later stage of the water invasion can be effectively simulated.

A method for determining parameters of a high-frequency vibrating mill with three grinding drums is disclosed. The mathematic modeling is established by applying the average parameter method and transfer function method; the synchronization-stability capability coefficient curve, and the dimensionless coupling torque maximum value diagram of the system are obtained by the characteristic analysis of synchronization and stability. Finally, the curves of rotational velocity of motors, displacements of mass bodies, and phase difference between exciters are obtained by the simulation, and the correctness of the method is verified by the comparison of characteristic analysis and simulation. The parameters of the high-frequency vibrating mill of the present invention can lower the technical requirements of exciters, reduce the loss of the exciters, increase the service life of the mill.

A method of detecting a lane line based on lidar data can include detecting, by a processor, points each estimated as a lane line in a lidar data, performing, by the processor, an estimation operation of estimating parameters of a mathematical model using the detected points, and performing, by the processor, a setting operation of calculating distances between each of the detected points and the mathematical model in which the parameters are estimated and setting the calculated distances as scores. The method can further include performing, by the processor, a summation operation of summing the scores, and setting, by the processor, the mathematical model determined according to the summation score as a lane line.

The invention relates to the technical field of oilfield exploration, and discloses a 4D quantitative and intelligent diagnosis method and system for spatio-temporal evolution of oil-gas reservoir damage types and extent. The method includes: determining a characteristic parameter characterizing reservoir damage by each of a plurality of factors based on a spatio-temporal evolution simulation equation of reservoir damage by each of the plurality of factors; and determining an effective characteristic parameter characterizing the damage extent of the reservoir based on the characteristic parameter characterizing reservoir damage rby each of the plurality of factors. The invention can quantitatively simulate the characteristic parameters of reservoir damage caused by the various factors and a total characteristic parameter of the reservoir damage. Therefore for a well without reservoir damage, performing quantitative prediction of reservoir damage and spatio-temporal deduction of damage laws is of scientific guidance significance for preventing reservoir damage, and formulating development plans for oil pools and subsequent well stimulation measures, and for a well with reservoir damage, also performing quantitative diagnosis of reservoir damage and spatio-temporal deduction of damage laws achieves optimal design of a declogging measure and improvement or restoration of oil-gas well production and water well injection capacity.

Example embodiments describe a computer-implemented method for balancing an electrochemical deposition of metal on a PCB substrate; the method including i) obtaining a layout of the metal on the PCB substrate comprising at least one active area having a circuit layout and a balancing area available for the balancing; ii) dividing the substrate area in a plurality of finite elements; iii) determining active metal fractions from the layout for the respective finite elements; iv) determining metal balancing fractions covering respective finite elements in the balancing area based on the active metal fractions in finite elements in the at least one active area surrounding the respective finite element.