Towards a Formalism-Based Toolkit for Automotive Applications

The success of a number of projects has been shown to be significantly improved by the use of a formalism. However, there remains an open issue: to what extent can a development process based on a singular formal notation and method succeed. The majority of approaches demonstrate a low level of flexibility by attempting to use a single notation to express all of the different aspects encountered in software development. Often, these approaches leave a number of scalability issues open. We prefer a more eclectic approach. In our experience, the use of a formalism-based toolkit with adequate notations for each development phase is a viable solution. Following this principle, any specific notation is used only where and when it is really suitable and not necessarily over the entire software lifecycle. The approach explored in this article is perhaps slowly emerging in practice - we hope to accelerate its adoption. However, the major challenge is still finding the best way to instantiate it for each specific application scenario. In this work, we describe a development process and method for automotive applications which consists of five phases. The process recognizes the need for having adequate (and tailored) notations (Problem Frames, Requirements State Machine Language, and Event-B) for each development phase as well as direct traceability between the documents produced during each phase. This allows for a stepwise verification/validation of the system under development. The ideas for the formal development method have evolved over two significant case studies carried out in the DEPLOY project

Simulation Study of a Heuristic Predictive Optimization Scheme for Grid-Reactive Heat Pump Operation

A heuristic predictive optimization scheme for gridreactive heat pump operation is introduced in this paper. It is based on thermal demand predictions (domestic hot water, heating demand) and does not require any numerical optimization which makes it easy to implement on real hardware. It follows the idea to use the heat pump to overheat the existing hot water storage in times of cheap electrical energy (oversupply). This way, converting electrical into thermal energy allows to economically shift electrical loads and hence to react at grid needs. The proposed optimization scheme is evaluated in a simulation study based on the simulation platform TRNSYS. A detailed evaluation of the algorithm in different application scenarios has been conducted by using a comprehensive system model of the investigated solar heat pump system. The evaluation presents the impact of different characteristics of the incentivizing price signal as well as prediction errors onto the load shifting and cost saving potential

Simulation Study of a Heuristic Predictive Optimization Scheme for Grid-Reactive Heat Pump Operation

A heuristic predictive optimization scheme for grid- reactive heat pump operation is introduced in this paper. It is based on thermal demand predictions (domestic hot water, heating demand) and does not require any numerical optimization which makes it easy to implement on real hardware. It follows the idea to use the heat pump to overheat the existing hot water storage in times of cheap electrical energy (oversupply). This way, converting electrical into thermal energy allows to economically shift electrical loads and hence to react at grid needs. The proposed optimization scheme is evaluated in a simulation study based on the simulation platform TRNSYS. A detailed evaluation of the algorithm in different application scenarios has been conducted by using a comprehensive system model of the investigated solar heat pump system. The evaluation presents the impact of different characteristics of the incentivizing price signal as well as prediction errors onto the load shifting and cost saving potential

De novo mutations across 1,465 diverse genomes reveal mutational insights and reductions in the Amish founder population

De novo mutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole-genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) Program, we called 93,325 single-nucleotide DNMs across 1,465 trios from an array of diverse human populations, and used them to directly estimate and analyze DNM counts, rates, and spectra. We find a significant positive correlation between local recombination rate and local DNM rate, and that DNM rate explains a substantial portion (8.98 to 34.92%, depending on the model) of the genome-wide variation in population-level genetic variation from 41K unrelated TOPMed samples. Genome-wide heterozygosity does correlate with DNM rate, but only explains <1% of variation. While we are underpowered to see small differences, we do not find significant differences in DNM rate between individuals of European, African, and Latino ancestry, nor across ancestrally distinct segments within admixed individuals. However, we did find significantly fewer DNMs in Amish individuals, even when compared with other Europeans, and even after accounting for parental age and sequencing center. Specifically, we found significant reductions in the number of C→A and T→C mutations in the Amish, which seem to underpin their overall reduction in DNMs. Finally, we calculated near-zero estimates of narrow sense heritability (h2), which suggest that variation in DNM rate is significantly shaped by nonadditive genetic effects and the environment