Disclosed are computer implemented techniques for correcting for numerically generated pressure waves at an inlet of a simulation space. The techniques include receiving a model of a simulation space and applying an inlet pressure to an inlet of the simulation space. The applied inlet pressure generates fluctuating velocities that produce undesired, numerically-generated pressure waves. The numerically generated pressure waves are measured to establish a measured pressure history. The measured pressure history is subtracted from the applied inlet boundary pressure history to provide a set of boundary conditions. The process conducts a fluid simulation using the set of boundary conditions. The process repeats using a subsequent set of boundary conditions, until an iteration is reached where the measured pressures near the inlet are sufficiently small to compensate for undesired, numerically-generated pressure waves, and thereafter stores that subsequent set of boundary conditions to provide a corrected set of boundary conditions.

Embodiments disclosed herein generally relate to a method and system for oil and gas predictive analytics. A computer system receives a set of production information for a well located in a region. The computing system generates a set of general reference groups comprising one or more reference wells for the region. The computing system determines whether the set of production information for the well includes the threshold amount of production information. The computing system selects a subset of reference wells from the general reference groups based on one or more traits of the well. The computing system generates a reference curve based on the set of production information associated with each reference well in the subset of reference wells. The computing system fits a decline curve to the reference curve, to determine an estimated ultimate recovery of the well.

A method for simulating a flow in which a structure is submerged, the method being implemented by computer, and the behavior of the structure in the flow being modeled by radial and rotational sources generating a velocity field representing the flow around the structure.

Methods and systems for designing a photonic computational architecture including a plurality of optical components. At least some of the methods include: defining a loss function within a simulation space composed of a plurality of voxels, the simulation space encompassing the plurality of optical components; defining an initial structure for the photonic computational architecture in the simulation space, at least some of the voxels corresponding to each of the plurality of optical components and having a dimension smaller than an operative wavelength of the computational architecture; determining values for at least one structural parameter and/or at least one functional parameter for each of the plurality of optical components using a numerical solver to solve Maxwell's equations; and defining a final structure of the photonic computational architecture based on the values for the one or more structural and/or functional parameters.

A numerical experimental method for urban waterlogging includes the following steps: acquiring raw data of an urban underlying surface; batch-processing urban waterlogging modeling data; batch-running urban waterlogging numerical experimental models; batch-processing urban waterlogging numerical experimental results; and displaying and analyzing the batch-processed urban waterlogging numerical experimental results. The numerical experimental method constructs a numerical experimental process, which can perform an unlimited number of repeated experiments in the numerical simulation process of urban waterlogging and achieve batch-running of data preprocessing, model operation, and data post-processing processes. Therefore, the numerical experimental method has the advantages of high efficiency, high convenience, high reliability, and low cost.

Refining an ecological niche model (ENM) associated with a geospatial location includes developing a fluid dynamics model based on measurements generated by a device deployed into fluid flows of the geospatial location. The measurements include temperature and velocity field, depth and particle transport measurements. The refining further includes refining and running the fluid dynamics model using measurements regenerated from the device being redeployed into the fluid flows to produce an output. This output is descriptive of fluid dynamics at the geospatial location and input into the ENM. The ENM is run to produce a baseline ENM output descriptive of a probability of a species existing at the geospatial location. In addition, the ENM is run with a limnologic modification to produce a predictive ENM output descriptive of a predictive probability of the species existing at the geospatial location that is comparable to the baseline ENM output.

Techniques for simulating fluid flow using a lattice Boltzmann (LB) approach for solving scalar transport equations and solving for total energy are described. In addition to the lattice Boltzmann functions for fluid flow the techniques include modifying a set of state vectors of the particles by adding specific total energy to states of particles that will be advected and subtracting the specific total energy from states of particles that will not be advected over a time interval and performing advection of the particles according to the modified set of states.

In an example, a method includes obtaining an indication of a deviation from an expected dimension of at least one dimension of an object generated using an additive manufacturing apparatus. A geometrical compensation model to apply to object model data for generating objects using additive manufacturing to compensate for anticipated deviations in dimensions may be determined from the obtained indication. The geometrical compensation model may comprise a first value to apply to object model data to modify a specification of an external dimension; and a second, different, value to apply to object model data to modify a specification of an internal dimension.

The present disclosure relates to a prediction method and system for an initiation volume of a debris flow slope source. The prediction method includes: dividing a debris flow source slope to be predicted into soil columns; determining a positional relationship between a selected central soil column and six adjacent soil columns around; calculating a most unfavorable sliding surface of the soil column and an unbalanced force on the sliding surface according to an upper bound theorem of a limit analysis; determining whether the most unfavorable sliding surface is unstable; determining a mode and a size of a force exerted by an unstable soil column on a surrounding soil column according to a break status of a connection bond of a lateral tensile stress of the central soil column; and finally determining whether the soil column is fluidized, and predicting an initiation volume of the debris flow source slope.

A method comprising performing simulations to determine energy transfer between the bulk fluid motion of gases through a combustion chamber and resonant acoustic modes of the combustion chamber using a simulation model. The method also comprises configuring one or more combustion chamber parameters for the simulation model to shape the resonant acoustic modes to diminish coupling between the resonant acoustic modes and driving mechanisms at a head portion of the combustion chamber and to enhance coupling between the resonant acoustic modes and damping mechanisms at an aft portion of the combustion chamber. The method further comprises determining whether the combustion chamber meets a predetermined performance level in response to determining that the combustion chamber meets a predetermined combustion stability level.