Plane wave/pseudopotential implementation of excited state gradients in density functional linear response theory: a new route via implicit differentiation

This work presents the formalism and implementation of excited state nuclear forces within density functional linear response theory (TDDFT) using a plane wave basis set. An implicit differentiation technique is developed for computing nonadiabatic coupling between Kohn-Sham molecular orbital wavefunctions as well as gradients of orbital energies which are then used to calculate excited state nuclear forces. The algorithm has been implemented in a plane wave/pseudopotential code taking into account only a reduced active subspace of molecular orbitals. It is demonstrated for the H$_2$ and N$_2$ molecules that the analytical gradients rapidly converge to the exact forces when the active subspace of molecular orbitals approaches completeness

Progress in mixed Eulerian-Lagrangian finite element simulation of forming processes

A review is given of a mixed Eulerian-Lagrangian finite element method for simulation of forming processes. This method permits incremental adaptation of nodal point locations independently from the actual material displacements. Hence numerical difficulties due to large element distortions, as may occur when the updated Lagrange method is applied, can be avoided. Movement of (free) surfaces can be taken into account by adapting nodal surface points in a way that they remain on the surface. Hardening and other deformation path dependent properties are determined by incremental treatment of convective terms. A local and a weighed global smoothing procedure is introduced in order to avoid numerical instabilities and numerical diffusion. Prediction of contact phenomena such as gap openning and/or closing and sliding with friction is accomplished by a special contact element. The method is demonstrated by simulations of an upsetting process and a wire drawing process

Symbiotic Assembly Systems – A New Paradigm

AbstractAssembly systems have been pressed in recent years to provide highly adaptable and quickly deployable solutions in order to deal with unpredictable changes following market trends. This has led to the development of multiple paradigms, namely Flexible Assembly System, Holonic Assembly Systems, Evolvable Assembly Systems, Modular Assembly systems, etc. Mostly these focus on increasing availability of automation, however this focus has overshadowed the human element in assembly systems. The lack of a clear human element in these approaches resulted in non-necessary automation and increase complexity. This paper proposes a new paradigm of Symbiotic Assembly Systems (SAS) in order to integrate the human aspects into these developments. The motivation is human actors should be treated as an intrinsic component of assembly systems. This would result in a system that can take advantage of its component's individual strengths (human or machines), and create a symbiotic environment. Beyond machine automation, human interventions in the system need not only to be modelled as processes but also integrated into the whole system operation. The idea builds on biological systems and their ability to establish symbiotic environments resulting in optimal collaborations. This paper proposes the conceptual vision of Symbiotic Assembly Systems and identifies the necessary developments required to achieve such paradigm. Furthermore it reports on how the developments from other paradigms can be integrated into SAS. An illustrative example is presented to demonstrate the potential of this approach

A symbiotic human–machine learning approach for production ramp-up

Constantly shorter product lifecycles and the high number of product variants necessitate frequent production system reconfigurations and changeovers. Shortening ramp-up and changeover times is essential to achieve the agility required to respond to these challenges. This work investigates a symbiotic human–machine environment, which combines a formal framework for capturing structured ramp-up experiences from expert production engineers with a reinforcement learning method to formulate effective ramp-up policies. Such learned policies have been shown to reduce unnecessary iterations in human decision-making processes by suggesting the most appropriate actions for different ramp-up states. One of the key challenges for machine learning based methods, particularly for episodic problems with complex state-spaces, such as ramp-up, is the exploration strategy that can maximize the information gain while minimizing the number of exploration steps required to find good policies. This paper proposes an exploration strategy for reinforcement learning, guided by a human expert. The proposed approach combines human intelligence with machine’s capability for processing data quickly, accurately, and reliably. The efficiency of the proposed human exploration guided machine learning strategy is assessed by comparing it with three machine-based exploration strategies. To test and compare the four strategies, a ramp-up emulator was built, based on system experimentation and user experience. The results of the experiments show that human-guided exploration can achieve close to optimal behavior, with far less data than what is needed for traditional machine-based strategies

Möglichkeiten der Bekämpfung des Falschen Mehltaus an Gurke (Pseudoperonospora cubensis) mit alternativen Präparaten

In organic cucumber production the infection with downy mildew (Pseudoperonospora cubensis) is one of the major problems. Use of biological control agents based on plant extracts and antagonistic micro organisms may be one possibility to control the disease. Plant extracts from Salvia officinalis and a plant belonging to the family Fabaceae (P1), as well as cultures of Brevibacillus brevis showed, in bioassays on potted cucumber plants, high potential to control the disease with efficacies between 55% and 100%. For S. officinalis extract the efficacy was close to 100% even at a concentration of 0.1325%. Initial trials under commercial growing conditions showed that the control of P. cubensis is better in protected than in open field production. In order to optimise the efficacy of the preparations for use in commercial cucumber production, further investigations on the mode of action, the active ingredients etc. are under way

Excited state tautomerism of the DNA base guanine: a restricted open-shell Kohn-Sham study

The relative stabilities of the six lowest energy tautomers of the DNA base guanine have been investigated in the first excite

Süßholz (Glycyrrhiza glabra) - Extrakt zur Regulierung von Falschem Mehltau im Öko-Gemüseanbau

A raw extract of licorice (Glycyrrhiza glabra) was tested against downy mildew in vegetables under semi-commercial conditions. In two greenhouse trials in cucumber, efficacies of ca. 70% were achieved (3% extract concentration) in either 7 or 10-11 day application intervals. Under open field conditions, weekly treatments resulted in ca. 2 week retardation of disease. In open field trials in lettuce, efficacies after weekly application of 5% G. glabra extract were variable, depending on disease pressure. In contrast, on lettuce seedlings in climate chambers, the extract reduced disease incidence of Bremia lactucae by 66 to 100%. In onion, applications of the extract at 6% concentration failed to control Peronospora destructor, despite of high efficacies under controlled conditions in the greenhouse. Overall, the G. glabra raw extract was highly effective in protected vegetables. Under field conditions low efficacies were most likely due to reduced rain fastness or UV-stability