Abstract: A method and circuit for an Automatic Self Checking and Healing (ASCH) of Physically Unclonable Functions (PUFs), the method includes: controlling a skew input added to each PUF cell of a PUF array in a circuit with sub-mV resolution; healing a portion of unstable bits of each PUF cells locally; and performing a second self-checking on healed PUF cells to determine final PUF cells to discard. The method further includes performing at least one of a static operation mode, a dynamic operation mode, and a hybrid operation mode of ASCH stabilization system based on design needs to reconfigure and mask the PUF array to achieve less than 1E-8 Bit Error Rate (BER) with less than 25% masking ratio. The circuit includes the skew input, a self-checking controller, a high-speed readout, a validity detector, and a Digital-to-Analog Converter (DAC).

Abstract: A digital simulation system of a power distribution network, comprising: a client and a server end. The server end is a simulation server cluster composed of several simulation servers; the simulation server cluster and the client are mutually connected through a communication bus, wherein the client is configured to use a DCOM component to invoke a simulation service provided by the server end, and the server end is configured to distribute a task to be processed to each cluster node. Constructing the above-mentioned digital simulation system facilitates an optimal planning and operation of a smart power distribution network, thereby improving the utilization efficiency and reliability of the smart power distribution network and reducing the loss of a power outage.

Abstract: A method of predicting the operation reliability of a distribution network, the method being based on an ARIMA model. By establishing an ARIMA model predict a user monthly power outage count; convert a non-smooth element outage count time series to a smooth time series; perform regression on only lagged values of a dependent variable, and on current values and lagged values of a stochastic error term, so as to establish a user monthly power outage count model; according to a prediction result sample an outage point, and at the same time, taking into account a real time load operating state, establish a failure mode effects table based on TLOC criteria and PLOC criteria; and calculate a system recovery time for each instance of device outage, and finally obtain a whole-year reliability index.

Abstract: An embodiment provides a multi-time-scale Digital/Analog (D/A) hybrid simulation system and simulation method therefor for a complex power distribution network and a computer storage medium, and is intended to solve existing problems about multi-time-scale modeling and simulation of the complex power distribution network and simulation accuracy and efficiency of the complex power distribution network.

Abstract: An embodiment provides a multi-time-scale Digital/Analog (D/A) hybrid simulation system and simulation method therefor for a complex power distribution network and a computer storage medium, and is intended to solve existing problems about multi-time-scale modeling and simulation of the complex power distribution network and simulation accuracy and efficiency of the complex power distribution network.

Abstract: A digital simulation system of a power distribution network, comprising: a client and a server end. The server end is a simulation server cluster composed of several simulation servers; the simulation server cluster and the client are mutually connected through a communication bus, wherein the client is configured to use a DCOM component to invoke a simulation service provided by the server end, and the server end is configured to distribute a task to be processed to each cluster node. Constructing the above-mentioned digital simulation system facilitates an optimal planning and operation of a smart power distribution network, thereby improving the utilization efficiency and reliability of the smart power distribution network and reducing the loss of a power outage.

Abstract: A method of predicting the operation reliability of a distribution network, the method being based on an ARIMA model. By establishing an ARIMA model predict a user monthly power outage count; convert a non-smooth element outage count time series to a smooth time series; perform regression on only lagged values of a dependent variable, and on current values and lagged values of a stochastic error term, so as to establish a user monthly power outage count model; according to a prediction result sample an outage point, and at the same time, taking into account a real time load operating state, establish a failure mode effects table based on TLOC criteria and PLOC criteria; and calculate a system recovery time for each instance of device outage, and finally obtain a whole-year reliability index.

Abstract: Methods for generating molecular formula distributions beyond a predetermined threshold for a petroleum stream are disclosed. An initial molecular formula distribution within a predetermined threshold is obtained for a petroleum stream. A correlation between two or more molecular properties of the initial molecular formula distribution is identified, and the initial molecular formula distribution is extrapolated beyond the predetermined threshold along the correlation. The extrapolated molecular formula is renormalized based on renormalization data obtained from the sample. The renormalized molecular formula distribution can then be blended with the initial molecular formula distribution, reconciled to secondary analytical measurements, and/or used to create a model of composition and/or a molecular composition-based model of a resid upgrading process. Systems for implementing the methods are also disclosed.

Abstract: Method for determining the composition of a material, including obtaining a reference model of composition (MoC) of the material based on a molecular formula distribution of the material, and reconciling, using at least one computer processor, the reference MoC to match at least one target property of the material, is provided. The reference MoC can be expressed as a combination of molecular lumps with associated reference percent. The reconciliation can be carried out using by constrained optimization of information entropy, and the optimization can be performed on a more coarse-grained basis relative to the reference MoC.

Abstract: Method for determining the composition of a material, including obtaining a reference model of composition (MoC) of the material based on a molecular formula distribution of the material, and reconciling, using at least one computer processor, the reference MoC to match at least one target property of the material, is provided. The reference MoC can be expressed as a combination of molecular lumps with associated reference percent. The reconciliation can be carried out using by constrained optimization of information entropy, and the optimization can be performed on a more coarse-grained basis relative to the reference MoC.

Abstract: Methods for generating molecular formula distributions beyond a predetermined threshold for a petroleum stream are disclosed. An initial molecular formula distribution within a predetermined threshold is obtained for a petroleum stream. A correlation between two or more molecular properties of the initial molecular formula distribution is identified, and the initial molecular formula distribution is extrapolated beyond the predetermined threshold along the correlation. The extrapolated molecular formula is renormalized based on renormalized based on renormalization data obtained from the sample. The renormalized molecular formula distribution can then be blended with the initial molecular formula distribution, reconciled to secondary analytical measurements, and/or used to create a model of composition and/or a molecular composition-based model of a resid upgrading process. Systems for implementing the methods are also disclosed.