Bernhard Middendorf

Bio: Bernhard Middendorf is an academic researcher from University of Kassel. The author has contributed to research in topics: Materials science & Medicine. The author has an hindex of 12, co-authored 65 publications receiving 1173 citations. Previous affiliations of Bernhard Middendorf include Central University, India & Technical University of Dortmund.

Investigative methods for the characterisation of historic mortars—Part 1: Mineralogical characterisation

Abstract: In addition to the mineralogical characterisation of components of binder and aggregate in historic mortars, it is sometimes necessary to perform a chemical analysis on the materials in historic mortars. Acid dissolution/separation of binder from aggregate is the simplest method, and allows the determination of the chemical composition of the acid-soluble binder and, after separation, information on the mortar’s aggregate. It is limited, when aggregate is acid-soluble. A range of significant analysis can be made including for soluble silica that relates to hydrated calcium silicates in the binder, and thus the hydraulicity of the binder. Other wet chemical analyses can be performed on the acid filtrate for soluble oxides of Fe, Al, Ca, Mg, S, Na and K. There may also be a requirement for the identification of organic substances, pigments and salts within a historic mortar. Chemical analysis forms a 2nd part of a possible scheme of characterisation of historic mortars that is presented as a flowchart. Chemical analysis also satisfies requirements for information input to conservation, repair and restoration works on historic buildings for the choice of compatible replacement materials. Corroboration of evidence of identification and quantification for chemical composition is best supported by a combination of methods, including mineralogical analysis methods. All methods of characterisation require qualified and experienced people to carry out the analyses.

Influence of silica fume on properties of fresh and hardened ultra-high performance concrete based on alkali-activated slag

Abstract: Based on the principles of ultra-high performance concrete (UHPC) a Portland cement free, alkali-activated material was optimized in order to enhance strength and durability. The formulation is based on ground granulated blast furnace slag and as an activator a combination of potassium water-glass and potassium hydroxide was used. Furthermore, silica fume and metakaolin as inorganic fines were used to increase the packing density of the mixture. Quartz sand (0–2 mm) and quartz powder were added as aggregates. The results comprise an enhancement of the rheological properties by the stepwise increase of silica fume. A w/b ratio of less than 0.25 was realised using a certain mixing procedure with a high intensity mixer. The compressive strength reaches values comparable with the strength range of an UHPC. The already low capillary porosity could further be decreased by the substitution of slag with a small amount of metakaolin, which is leading to a higher polymerisation degree due to an incorporation of aluminium in the reaction products. The enhanced polymerisation degree was estimated by FTIR and XRD. Although no effective superplasticizer can be used in this high alkaline material, the low w/b ratio and a good workability can be achieved by using certain amounts of silica fume.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.