Abstract: Embodiments for dynamically distributing loads in computational rendering in a computing environment. A computational rendering model on a computational rendering to exploit nested recursive parallelism within a heterogenous computing architecture to enable communication overlap, memory transfer, and data and task management, wherein the computational rendering model is developed for the heterogenous computing architecture.

Abstract: Embodiments for providing activity feedback are provided. Information associated with a user performing an activity is received. A user biomechanical representation is generated based on the received information. A corpus associated with the activity is analyzed. An ideal biomechanical representation is generated based on the analyzing of the corpus associated with the activity. The user biomechanical representation is compared to the ideal biomechanical representation. Feedback for the user is generated based on the comparison of the user biomechanical model to the ideal biomechanical representation.

Abstract: The protection of water providing entities from loss due to environmental events is disclosed including receiving structured and unstructured data related to a water resource, generating time series for a plurality of index items, generating training data and testing data based on the time series for the plurality of index items, determining correlations between the time series of the index items using the generated training data, determining a classification boundary as a strike level based on the determined correlation, generating a protection strategy based on the strike level, applying the protection strategy to the testing data to generate a resulting data time series, and presenting the resulting data time series via a display of a computing device to at least one user of the computing device.

Abstract: Embodiments for generating text with a target style are provided. A target corpus is analyzed to determine a style representation associated with the target corpus. A source text is analyzed to determine a meaning representation associated with the source text. A target text is generated utilizing the target style representation associated with the target corpus and the meaning representation associated with the source text.

Abstract: Embodiments for estimating ice formation and depth by a processor. Ice formation and ice depth of a selected region of water may be cognitively forecasted using a prediction model such that the prediction model identifies similar characteristics between the selected region of water and one or more alternative regions of water by analyzing content of one or more data sources associated with an ontology of concepts representing a domain knowledge related to the selected region of water and the one or more alternative regions.

Abstract: Embodiments for implementing intelligent vessel trajectory planning and adapting by a processor. A trajectory of a vessel may be dynamically determined according to forecasted wave conditions using a surrogate wave model, a wave forecasting model, one or more user defined constraints, or a combination thereof.

Abstract: A simulation model recovery method, system, and computer program product include initiating a simulation model, during an operation of a model, periodically writing a solution space of the model to a checkpoint restart file, during an operation of the model, periodically writing diagnostic information on model progression to a log file, detecting a failure of the model, based on the log of the model, determining a time of the failure, based on the model outputs and restart files, determining a period of a numerical instability preceding the failure, selecting a checkpoint of the model preceding the period of the numerical instability, based on the numerical instability and diagnostic information in log files, modifying a configuration of the model, and restarting the model based on the selected checkpoint and the modified configuration.

Abstract: A method and system for outputting a state of a physical system using a calibrated model of the physical system, where the calibrated model is used to generate a model prediction. The system includes a plurality of sensors connected to a routing node are used to monitor measured data of the physical system. A first sensor of the plurality of sensors includes a logic module configured to determine an uncertainty quantification, and to combine the uncertainty quantification with the model prediction to output the state of the physical system.

Abstract: Embodiments for dynamically distributing loads in computational rendering in a computing environment. A computational rendering model on a computational rendering to exploit nested recursive parallelism within a heterogenous computing architecture to enable communication overlap, memory transfer, and data and task management, wherein the computational rendering model is developed for the heterogenous computing architecture.

Abstract: A mechanism is provided in a data processing system for minimizing uncertainty envelopes in trajectories of evolving ensemble members. The mechanism generates a trajectory forecast of each member object of an ensemble based on an initial state-space and a model for predicting trajectories of the member objects to generate a plurality of trajectory forecasts. Each of the plurality of trajectory forecasts has an individual uncertainty envelope. The mechanism applies a classification algorithm on the plurality of trajectory forecasts to identify at least one group of member objects having similar trajectory forecasts, generates a reduced ensemble of member objects including the identified group of member objects, and reconfigures the state-space and the model for predicting trajectories. The mechanism generates an updated trajectory forecast of each member object of the reduced ensemble based on the reconfigured state-space and the reconfigured model for predicting trajectories of the member objects.

Abstract: Embodiments for intelligent forecasting of material concentrations in a fluid by a processor in a computing environment. A material concentration of a material in a fluid may be predicted according to one or more continuous stirred tank reactor (CSTR) surrogate models on statistical flow trajectories of the fluid defined by a principle component analysis (PCA) operation of a system.

Abstract: A simulation model recovery method, system, and computer program product include initiating a simulation model, during an operation of a model, periodically writing a solution space of the model to a checkpoint restart file, during an operation of the model, periodically writing diagnostic information on model progression to a log file, detecting a failure of the model, based on the log of the model, determining a time of the failure, based on the model outputs and restart files, determining a period of a numerical instability preceding the failure, selecting a checkpoint of the model preceding the period of the numerical instability, based on the numerical instability and diagnostic information in log files, modifying a configuration of the model, and restarting the model based on the selected checkpoint and the modified configuration.

Abstract: Embodiments for implementing intelligent vessel trajectory planning and adapting by a processor. A trajectory of a vessel may be dynamically determined according to forecasted wave conditions using a surrogate wave model, a wave forecasting model, one or more user defined constraints, or a combination thereof.

Abstract: A method, computer program product and computer system to generate safety alerts is provided. A processor retrieves a plurality of measurements associated with a location. A processor determines a set of features based on the plurality of measurements. A processor identifies a set of membership functions for the set of features. A processor determines a safety index for the body of water based on the set of membership functions and one or more input value ranges for the set of features. In response to the safety index being above a threshold value, a processor sends an alert to one or more users regarding the location.

Abstract: A fluid is modeled as a set of discrete particles. Each of the particles is associated with one or more properties, and a spatial distance comprising a smoothing length over which the one or more properties are to be smoothed. A corresponding trajectory is simulated for each of the particles. The corresponding trajectory is used to formulate a first solution for simulating transport within the fluid. A first predicted error is determined for the first solution. An iterative adjustment is performed to at least one of: a quantity of particles, the smoothing length, or the one or more corresponding properties, to formulate a second solution for simulating transport with the fluid, and a second predicted error is determined for the second solution, until the second predicted error is within a predefined boundary.

Abstract: Embodiments for deep learning for partial differential equation (PDE)-based models by a processor. A trained forecasting model and consistency constraints may be generated using a PDE-based model, a discretization of the PDE-based model, historical inputs the of the PDE-based model, and a representation of consistency constraints to generate a predictive output.

Abstract: Embodiments for managing a wave energy converter (WEC) device by one or more processors are described. At least one environmental characteristic associated with a WEC device in a body of water is received. A prediction of wave conditions on the body of water is calculated based on the at least one environmental characteristic. A signal representative of the prediction of wave conditions is generated.

Abstract: A computer system, method, and computer readable product are provided for cognitive initialization of large-scale advection-diffusion models. In various embodiments, parameters are identified for configuring an advection-diffusion model to be run. Then a natural language processing search is conducted for these parameters in relevant literature to find corresponding numerical values. These search results are compared, and values for the parameters are set for the advection-diffusion model, and the model is run.

Abstract: Embodiments for managing aquaculture production by one or more processors are described. Information associated with an aquaculture site is received. The information includes at least a current stocking density of the aquaculture site. A recommended time for harvesting is determined based on the received information. A signal representative of the recommended time for harvesting is generated.

Abstract: A mechanism is provided for targeted, iterative refinement of advection-diffusion model grid resolution. A simulation is executed of advection-diffusion processes for an area associated with a user-defined location. Responsive to detecting an event within a subset of cells of a first set of cells, the subset of cells is refined such that each of the subset of cells is gridded to comprise a second set of cells with dimensions less than the first set of cells. A number of run-time floating-point operations per second (FLOPS) of the model is computed for each of the first set of cells and the second set of cells. Based on a collective time associated with a computed number of FLOPS failing to exceed the user-defined constraint, the simulation continues to execute with the first set of cells and the second set of cells. The process is repeated until a predetermined resolution value is met.