A fast GPU Monte Carlo Radiative Heat Transfer Implementation for Coupling with Direct Numerical Simulation

We implemented a fast Reciprocal Monte Carlo algorithm, to accurately solve radiative heat transfer in turbulent flows of non-grey participating media that can be coupled to fully resolved turbulent flows, namely to Direct Numerical Simulation (DNS). The spectrally varying absorption coefficient is treated in a narrow-band fashion with a correlated-k distribution. The implementation is verified with analytical solutions and validated with results from literature and line-by-line Monte Carlo computations. The method is implemented on GPU with a thorough attention to memory transfer and computational efficiency. The bottlenecks that dominate the computational expenses are addressed and several techniques are proposed to optimize the GPU execution. By implementing the proposed algorithmic accelerations, a speed-up of up to 3 orders of magnitude can be achieved, while maintaining the same accuracy

Engineering valuation of blockchain technology in the context of petroleum supply chain: A real options approach

In this paper, we mathematically model and analyze occurrence of trade disputes in the context of a petroleum supply chain network which includes a seller, a buyer and an arbitrator. We study how switching from conventional trading system to a blockchain-based system could help decrease the number of disputes while maintaining the profitability of trading. Specifically, we determine what is the optimal timing to switch to blockchain technology through arbitrator’s perspective under petroleum price uncertainty. The way blockchain technology aids trade irrefutability is to provide a secure and immutable distributed ledger which ensures each trade is recorded and timestamped with no participant being able to alter the transactions history. Consequently, participants trading in a safe network, can trust the system and conduct transactions more securely. Currently, around nine percent of crude oil transactions are disputed, which equates to around USD 150 billion each year. In a petroleum trading network, the disputes filed by either seller or buyer are consequences of fraud and/or error. Studies have shown, integrating Blockchain technology into trading network significantly reduces the probability of transactions disputes and trades recorded on a blockchain distributed ledger has higher finality rates. Although there has been much interest in blockchain technology applicable to petroleum industry supply chain, there has been little analytical investigation of irrefutability, one of the critical attributes of the blockchain technology. Irrefutability corresponds to a network characteristic which prevents any participant to question the integrity of transactions recorded on ledger and any future disputes. Throughout this work, we aim to show how irrefutability can be valued, in the context of petroleum industry supply chain, from a perspective of stochastic optimal control. We will show how petroleum strike prices for switching to blockchain technology can be found via real options approach through modeling fraud uncertainty. In other words, we are going to demonstrate under what conditions it is economically feasible from arbitrator’s perspective to implement a blockchain technology by modeling number of disputes as a function of system’s reliability. Even though at a first glance arbitrator may have no reason to favor blockchain over traditional system because of decrease in dispute resolution payments due to increased trade finality, on the other hand we conclude a profit for arbitrator which is sourced in higher transaction verification fees as number of transactions increases due to improved reliability of the system