In-house Tool Research Articles

Development of a log file analysis tool for proton patient QA, system performance tracking, and delivered dose reconstruction.

To describe a log file-based patient-specific quality assurance (QA) method and develop an in-house tool for system performance tracking and dose reconstruction in pencil-beam scanning proton therapy that can be used for pre-treatment plan review. The software extracts beam-specific information from the treatment delivery log file and automatically compares the monitor units (MU), lateral position, and size of each spot against the intended values in the treatment plan to identify any discrepancies in the beam delivery. The software has been used to analyze 992 patients, 2004 plans, 4865 fields, and more than 32 million proton spots from 2016 to 2021. The composite doses of 10 craniospinal irradiation (CSI) plans were reconstructed based on the delivered spots and compared with the original plans as an offline plan review method. Over the course of 6 years, the proton delivery system has proved stable in delivering patient QA fields with proton energies of 69.4-221.3 MeV and an MU range of 0.003-1.473 MU per spot. The planned mean and standard deviation (SD) of the energy and spot MU were 114.4 ± 26.4 MeV and 0.010 ± 0.009 MU, respectively. The mean and SD of the differences in MU and position between the delivered and planned spots were 9.56 × 10-8 ± 2.0 × 10-4 MU and 0.029/-0.007 ± 0.049/0.044 mm on the X/Y-axis for random differences and 0.005/0.125 ± 0.189/0.175 mm on the X/Y-axis for systematic differences. The mean and SD of the difference between the commissioning and delivered spot sizes were 0.086/0.089 ± 0.131/0.166 mm on the X/Y-axis. A tool has been developed to extract crucial information about the performance of the proton delivery and monitor system and provide a dose reconstruction based on delivered spots for quality improvement. Each patient's plan was verified before treatment to ensure accurate and safe delivery within the delivery tolerance of the machine.

Seismic analysis of failure mechanisms in adjacent interacting stone masonry buildings via rigid block modeling

Groups of contiguous unreinforced stone masonry buildings are a common type of housing seen in old European downtowns. However, assessing their response to earthquakes poses several challenges to the analysts, especially when the housing units are laid out in compact configurations. In fact, in those circumstances a modeling technique that allows for the dynamic interaction of the units is required. The numerical study carried out in this paper makes use of a rigid block modeling approach implemented into in-house software tools to simulate the static behavior and dynamic response of an aggregate stone masonry building. Said approach is used to reproduce the results of bi-axial shake-table tests that were performed on a building prototype as part of the activities organized within the Adjacent Interacting Masonry Structures project, sponsored by the Seismology and Earthquake Engineering Research Infrastructure Alliance for Europe. The experimental mock-up consisted of two adjacent interacting units with matching layout but different height. Two rigid block models are used to investigate the seismic response of the mock-up: a 3D model allowing for the limit analysis of the building on one hand, and a 2D model allowing for the non-linear static pushover and time-history analysis on the other. The 3D model was built for the blind prediction of the test results, as part of a competition organized to test different modeling approaches that are nowadays available to the analysts. The 2D model was implemented once the experimental data were made available, to deepen the investigation by non-linear static pushover and time-history analysis. In both models, the stonework is idealized into an assemblage of rigid blocks interacting via no-tension frictional interfaces, and mathematical programming is utilized to solve the optimization problems associated to the different types of analysis. Differences between numerical and experimental failure mechanisms, base shears, peak ground accelerations, and displacement histories are discussed. Potentialities and limitations of the adopted rigid block models for limit, pushover and time-history analyses are pointed out on the basis of their comparisons with the experimental results.

Data-driven modeling of high-speed centrifugal compressors for aircraft Environmental Control Systems

The Environmental Control System (ECS) is the main consumer of non-propulsive power onboard aircraft. The use of an electrically-driven Vapor Compression Cycle (VCC) system, in place of the conventional air cycle machine, can lead to a substantial increase of the coefficient of performance. This work documents the development of an integrated design optimization method for VCC-based aircraft ECS, where the sizing of the system is performed along with the conceptual design of the compact heat exchangers and the high-speed centrifugal compressor. A data-driven model of the compressor has been developed to reduce the complexity of the VCC system model and the computational cost of the associated optimization problem. The model is based on artificial neural networks and has been trained on a synthetic dataset of 165k centrifugal compressor designs, generated with an in-house tool. The case study selected to demonstrate the capabilities of the proposed methodology is the multi-objective design optimization of an electrically-driven VCC system for the ECS of a single-aisle, short-haul aircraft, flying at cruise conditions. The results show that the number of function evaluations needed to identify the Pareto front reduces by a factor of three when using the data-driven model, in place of a meanline method. At the same time, the robustness of the numerical solver is improved, leading to the identification of optimal solutions covering a wider design space. Finally, the proposed methodology enables the analysis of the trends established between the system performance metrics and the design of the individual components.

Process design analysis of a hybrid power-and-biomass-to-liquid process – An approach combining life cycle and techno-economic assessment

Techno-economically and ecologically optimized processes require understanding of trade-offs between efficiencies, costs and environmental impacts. For this purpose, DLR’s in-house tool TEPET for techno-economic analysis was enhanced to enable simultaneous life cycle assessment (LCA). Within this study a hybrid Power-and-Biomass-to-Liquid concept is analysed that can switch between a biomass alone and hydrogen enhanced operation. In order to integrate the techno-economic and ecological results, a dimensionless cost-impact factor is introduced, which gets minimised when both costs and environmental impacts are low. The methodology is applied to investigate process parameter variations within this process concept. The varied process parameters are H2/CO ratio, H2 conversion in the Fischer-Tropsch synthesis and CO2 recycle rate to the gasification. Furthermore, the influence of LCA allocation methods on the preferable set of process parameters was examined. Results show a correlation of lowest environmental impact with high fuel efficiency (energetic fuel output per overall energetic input) for economic allocation. For energetic allocation, high process efficiency (ratio of overall energetic output to overall energetic input) leads to the lowest environmental impact. High carbon efficiency is especially important when biomass has a big impact on a certain category. Sensitivity studies for the global warming potential demonstrate a low sensitivity to the investigated process parameter variations compared with changes in input parameters like biomass and electricity source or transport distance. As the net production cost (NPC) are more sensitive towards the process parameter variations, the cost-impact factor is lowest for the set of process parameters with the lowest NPC.

Exhaust Gas Recirculation (EGR) analysis of a swirl-stabilized pulverized coal flame with focus on NOx release using FPV-LES

Highly-resolved Large Eddy Simulations (LES) are performed to investigate the combustion characteristics and the NOx-formation in the swirl-induced recirculation zones of the Brigham Young University (BYU) Burner Flow Reactor (BFR). The simulations are performed using the in-house LES tool PsiPhi, utilizing a flamelet/progress variable (FPV) approach to model the reactive multiphase flow. Four dimensions are used to parameterize the thermochemical quantities consisting of two mixture fractions for volatiles and char burnout, the total enthalpy and a progress variable, defined by a linear combination of key product species mass fractions. A reduced CRECK mechanism with 120 species and 1551 reactions is used, including all NOx-formation mechanisms (prompt-, fuel-, thermal-, and pathway via N2O). Devolatilization, char burnout and radiation effects are considered in the LES. Radial profiles of major gas species are compared with experimental data, leading to an overall good agreement. Two variants to determine NO species were investigated: (1) the direct extraction of NO from the flamelet table and (2) the solution of an additional transport equation for NO with a modified NO source term, split into a formation and a rescaled consumption part. The solution of an additional transport equation for NO is clearly superior and necessary for pulverized coal simulations, showing a much improved prediction of forward- and backward reactions of NO inside the furnace, while the direct extraction of NO from the flamelet table greatly overpredicts its formation.

Prevalence and founder effect of DRC1 exon 1-4 deletion in Korean patients with primary ciliary dyskinesia.

Primary ciliary dyskinesia (PCD) is a genetically heterogeneous disorder affecting ciliary structure and function. PCD exhibiting dynein regulatory complex subunit 1 (DRC1) exon 1-4 deletion has been reported in several Japanese PCD patients; however, no large scale studies have been performed. Here, we aimed to determine the prevalence and founder effect of this variant in the Korean population. Using an in-house copy number variation tool, we screened for DRC1 exon 1-4 deletion in 20 patients with PCD and exome data of 1435 patients in the Seoul National University Hospital repository. In cases of suspected DRC1 deletion, confirmatory gap-PCR was performed. In a PCD cohort, three of 20 (15%) patients were positive for DRC1 exon 1-4 deletion (NM_145038.5(DRC1): c.1-3952_540 + 1331del27748-bp) while pathogenic variants were found in CCDC39 (N = 1), DNAAF6 (N = 1), DNAH9 (N = 1). In the 1,435-sample exome data, seven patients (0.49%) were confirmed to have DRC1 exon 1-4 deletion. A chimeric sequence including the junction was searched from the 1000 Genomes Project data repository. One Japanese patient (0.96%) was found to have the same DRC1 exon 1-4 deletion, which was absent in other populations. This study demonstrated that the DRC1 exon 1-4 deletion is a founder mutation based on haplotype analysis. In summary, the prevalence of PCD based on DRC1 exon 1-4 deletion is particularly high in Korean and Japanese populations, which is attributed to the founder effect. Genetic testing for DRC1 exon 1-4 deletion should be considered as an initial screening tool for Korean and Japanese patients with PCD.

An assessment of scenarios for transuranic burning and 233U production in a small molten chloride fast reactor

Molten Chloride Fast Reactor (MCFR) attracts more and more attention owing to its significantly hard neutron spectrum and high solubility for actinide trichlorides, making it an appealing option for burning transuranic (TRU) elements discharged from pressurized water reactors (PWRs). Meanwhile, in recent years, the development of thorium fuel cycle has aroused considerable interest worldwide with the purpose of saving uranium reserves and further reducing the production of long-lived minor actinides. A small MCFR incorporating TRU burning and 233U production is proposed in this work in order to evaluate its incineration and production capabilities. By employing an in-house developed tool based on SCALE 6.1, the fuel cycle features of the small MCFR with three fuel loading scenarios, including pure TRU (scenario 1), TRU plus depleted uranium (scenario 2) and TRU plus thorium (scenario 3), are analyzed. The evolution behaviors of main nuclides, reactivity worth, neutron spectra and temperature reactivity coefficient (TRC) are discussed in detail. It is found that the MCFR can burn TRU effectively and the transmutation rates for the three scenarios are 930 kg/GWe/year, 375 kg/GWe/year and 768 kg/GWe/year, respectively, achieving a maximum capability for TRU burning of about 3.7 times the annual TRU production in a 1-GWe PWR with 50 MWd/kgU discharge burnup. Meanwhile, scenario 3 has the highest 233U production capability of about 110.3 kg per year, although it does not offer processing advantages over scenario 1 and scenario 2. The analysis of TRC indicates that the fuel salt TRC and the total core TRC are both strongly negative for all three scenarios owing to the thermal expansion of liquid fuel salt. Finally, a nuclear energy system consisting of both fast and thermal molten salt reactors is proposed and evaluated to establish a closed nuclear fuel cycle with very low radioactive wastes.

Dynamics-based network analysis identifies laci rheostats with high accuracy.

One current challenge in protein engineering involves accurately predicting distal mutations which lead towards a desired function. A more complex problem is identifying and characterizing putative “rheostat” sites which result in progressive, amino acid-dependent biophysical changes upon substitution. The E. coli LacI system contains several rheostat positions with respect to the binding of LacI inducer IPTG, which allosterically inhibits DNA binding. Here we employ in-house computational tools for characterizing network dynamics: Site-specific flexibility via the Dynamic Flexibility Index (DFI), residue pair coupling strength via the Dynamic Coupling Index (DCI), and Vibrational Density of States (VDOS) analysis to generate measures of position-specific dynamic-based metrics. Comparison of bound and unbound LacI shows specific regions of each system exhibit fundamentally different flexibilities where critical DNA binding domain positions show increased flexibility when bound to IPTG. Further, we assess asymmetry in dynamic coupling as a cause-effect measure between ligands/ligand binding positions and all other positions within the protein. Additionally, it is possible to calculate positional vibrational entropy through VDOS; this analysis, again, showed distinctions between bound and unbound simulations in both the DNA binding domain as well as the IPTG binding region. Taken together, the drastic differences of these dynamics-based metrics between bound and unbound conformations indicate their strength in construction unique dynamical fingerprints for both systems. Using a machine learning approach, we construct features based off of these dynamic properties from which we extract probabilities of a given position being “neutral”, “toggle” (i.e., abolishing biophysical activity upon mutation) or “rheostat” based upon experimental IPTG EC50 data of IPTG binding. Using a small subset of dynamic network features, we show it is possible to categorize, with accuracy rates of ∼0.9, a given position's probability of falling into one of the three above categories.

Development of an engineering tool to analyze spectral fatigue of floating structures by means of hydro-elastic coupling

Navy vessels are relative long and slender ships which must withstand, during their extensive operational life, cyclic loads produced by the seaway. Fatigue is, hence, for those vessels a dominant parameter in the structural ship design and on their operation. Due to the arising complexity of fatigue assessments, an in-house tool is developed to perform automatized spectral fatigue analysis. Tool is called SEAFALT and stands for Long-Term Spectral Fatigue Analysis. This article described the calculation process of SEAFALT, together with results of a case of study. SEAFALT controls automatically the coupling process of the hydrodynamic load calculated on each sea scenario (via ANSYS AQWA), with its correspondent Finite-Element (FE) structural response (via ANSYS MAPDL). SEAFALT calculates: the expected long-term fatigue damage on each node of the FE-model and the minimum required FAT-class.

Coupled dynamic analysis of horizontal axis floating offshore wind turbines with a spar buoy floater

Coupled dynamic analysis of a floating offshore wind turbine (FOWT) is predicted with in-house ITU-WAVE computational tool. The hydrodynamic parameters are approximated with time marching of boundary integral equation whilst aerodynamic parameters are solved with unsteady blade element momentum method. In addition, forces on FOWT due to mooring lines are predicted with quasi-static analysis whilst hydrodynamic viscous effects are included with Morison equation. FOWT’s blades are considered as an elastic structure whilst tower is considered as a rigid structure. The effects of steady wind speed on surge motion spectrum decrease the spectrum amplitude over wave frequency ranges, but this effect is not significant. The duration of time domain simulation plays significant role in the region of surge and pitch resonant frequencies. The numerical results of in-house ITU-WAVE computational code for eigenfrequencies of blades, aerodynamics and hydrodynamics parameters are validated against other numerical results which shows satisfactory agreements.

Carbon Analysis, Life Cycle Assessment, and Prefabrication: A Case Study of a High-Rise Residential Built-to-Rent Development in the UK

Recent research relating to energy use and carbon emissions by buildings has started to move from operational energy carbon impacts to the embodied energy/carbon impacts of buildings, and the methods and approaches used in architectural design to reduce embodied carbon have become more prominent. From a practitioner’s perspective, working with an ‘in-house’ Life Cycle Assessment (LCA) tool has become a growing trend for architects, and one perceived way of improving the LCA outcomes of a proposed building is to consider prefabrication of the construction process. Initiatives such as the Low Energy Transformation Initiative (LETI) and government bodies such as Greater London Authorities (GLA) provide guidance on LCA and upfront carbon emission targets for transitioning to net zero by 2050. The aim of this study was to establish (i) the LCA impacts from prefabricated residential buildings against current benchmarks; (ii) boundaries and opportunities in architectural practice in the UK when conducting an LCA; (iii) the effectiveness of an in-house LCA tool. This study shows that, although the life-cycle emissions of this prefabricated building achieved a low band in the LETI labelling system, with 1076 kgCO2e/m², it still performs better than the business-as-usual model value of 1200 kgCO2e/m². The results also reveal that the construction industry is not ready to provide realistic data on the prefabrication process to test its advantages compared to conventional constructional methods. However, having an in-house LCA tool provides a faster and more comprehensive LCA due to the commitment to carbon assessment in the office and saves time compared to manual calculations.

Drag Reduction and Leidenfrost Effect on Submerged Ratcheted Cylinder

This paper presents experimental investigations of submerged self-propulsion due to the Leidenfrost effect. We aim to identify and quantify the forces governing the free-fall of heated cylinders at temperatures between 25 °C and 550 °C. Understanding the forces involved within three-phase systems is essential when designing sensitive instruments, such as microelectronic devices. Cylinders with sizes in the range of tens of millimeters are released into a vertical column filled with Novec 7000. Experiments were conducted to investigate five topological designs, and bored-out hollows within the cylinders forced vertical free-fall. The control cylinder was smooth, while the others had ratchet teeth engraved on their surface. Ratcheted cylinders were manufactured in pairs to compare ratchet directionality. An in-house tracking tool reduced experimental error and measurement noise. The time taken to reach terminal velocity increases with initial temperature while terminal velocity decreases, respectively. The depth at which terminal velocity occurs also decreases with increasing initial temperature. The existence of submerged self-propulsion has been identified by comparing ratcheted cylinders of opposing directionality. A theoretical mechanism for the action of the viscous friction force that drives self-propulsion has been developed. The viscous friction force has been quantified to be between 0.04–3.28 mN.

The Computation of Stiff and Elastic Features of Structures with Time Domain Analysis

Hydroelasticity of marine structures with and without forward speed is studied directly using time dependent Boundary Integral Equation Method with Neumann-Kelvin linearisation where the potential is considered as the impulsive velocity potential. The exciting and radiation hydrodynamic parameters are predicted in time with transient wave Green function whilst the structural analysis is solved with Euler-Bernoulli beam method at which modeshapes are defined analytically. The modal analysis is used to approximate the hydroelasticbehaviour of the floating systems through fully coupling of the structural and hydrodynamic analyses. As it is expected, it is found with numerical experience that the effects of the rigid body modes are greater than elastic modes in the case of stiff structures. The predicted numerical results of the present in-house computational tool ITU-WAVE are compared with experimental results for validation purposes and show the acceptable agreements.

Techno-economic analysis for the effects of electricity pricing system on the market competitiveness of cogeneration model

In this study, the actual operation status of the cogeneration model was investigated to examine the difference between the theoretical evaluation and the field operation situation. The adequacy of the installed capacity of the cogeneration system was assessed by using in-house developed diagnostic analysis simulation tool, and the effects of operational strategy on securing operational cost benefit under the progressive electricity rate system was also examined with event-based operating characteristic analysis. The installed prime mover was found to be designed excessively by an average of 47%, and the relative primary energy savings showed a large deviation in the range of 3–22% for each case. As a result of analyzing the effect of the rapid expansion of renewable energy on the operational performance, it was found that when the renewable power distribution ratio was increased to 30%, the relative primary energy savings effect fell to less than 5%. As an alternative, a hybrid cogeneration model integrated with heat pump was proposed, and it was confirmed that it could have the effect of mitigating the effect of expanding renewable energy.

On the sensitivity of PROMs during breast radiotherapy

PurposeTo investigate the sensitivity of patient-reported outcome measures (PROMs) to detect treatment-related side effects in patients with breast cancer undergoing external beam photon radiotherapy. MethodsAs part of daily clinical care, an in-house developed PROM tool was used to assess side effects in patients during a) whole-breast irradiation (WBI) to 40 Gy, b) WBI with a sequential boost of 10 Gy, and c) partial-breast irradiation (PBI) to 40 Gy. Results414 patients participated in this prospective study between October 2020 and January 2022, with 128 patients (31 %) receiving WBI, 241 (58 %) receiving WBI followed by a sequential boost, and 50 patients (12 %) receiving PBI. Significant differences in the reported toxicities (itching, radiation skin reaction, skin darkening, and tenderness and swelling) were reported between the WBI cohorts with and without boost (p < 0.001, p < 0.001, p < 0.001, and p = 0.002, respectively). The comparison of PBI with WBI (no-boost) yielded significant differences for radiation skin reaction (p < 0.001). ConclusionThe results highlight the high sensitivity of PROMs to detect treatment-related side effects in patients with breast cancer. Thus, PROMs may be a valuable tool for quality control and may support evidence-based learning from real-world data originating from daily routine care.

Dosimetric characteristics of the LIAC intraoperative radiotherapy beams: Assessment of sensitivity to measurement errors at the commissioning phase

Commissioning of the LIAC intraoperative electron radiotherapy (IOERT) unit relies on the vendor's SWL-LIAC software. This software simulates the percentage depth-doses (PDDs), off-axis dose profiles and relative output factors (ROFs) for all beams based on a small set of input measurements. To date, the impact of various possible measurement errors during commissioning on LIAC dosimetric characteristics has not been studied in detail. We aimed to assess the sensitivity of the dosimetric characteristics of the ‘LIAC 12 MeV’ IOERT unit beams to various measurement errors in the commissioning phase by obtaining the magnitude of the influence of each error.The required SWL-LIAC inputs (PDDs of applicator diameters 3, 7, and 10 cm and open field) were measured with intentional applicator misalignments including 1° rotation or lateral (2 mm) or vertical (±2 mm) displacements. Also, inaccurate water surface definition for the detector was simulated by using PDDs that were shifted by ±2 mm. The errors were applied one at a time. To identify the most influential errors, the computed relative dosimetric characteristics resulting from such erroneous measurement conditions were compared to the corresponding ‘error-free’ ones. The depths of 90% and 50% doses (R90 and R50, respectively) were investigated further.All the resulting errors in R90, R50, flatness, symmetry and penumbra were within 3.9 mm, 2.8 mm, 4.3%, 4.6% and 3.5 mm, respectively. The overall averages of the absolute differences in these indices from the error-free fields were 0.8 mm, 0.8 mm, 0.6%, 0.4% and 0.5 mm, respectively. Errors in water surface definition for the detector had 4.4 to 22 times greater influence on PDDs than the other errors. The corresponding values for the profiles were 1.3–5.8 times. Among the errors in applicator alignment, PDDs and profiles were more affected by rotational and vertical ‘stand-in’ applicator misalignments, respectively. The R90 and R50 values were less affected by the errors in the small (3 and 4 cm diameter) and 45° bevelled applicators.To conclude, on average, the studied errors caused relatively small changes in beam characteristics although the maximum magnitudes of the observed errors were fairly substantial. Among the investigated errors, defining the water surface inaccurately has the largest impact on the dosimetric characteristics. Overall, sensitivity to the studied errors was found to be greatest with large-diameter flat applicators and/or lower electron energies. Although individual errors in applicator alignment have less effect on dosimetric characteristics compared to water surface error, given that these errors may occur simultaneously during dosimetry, special attention should be paid to placing the applicator correctly at the surface. Special set-up aids, such as our in-house tool for aligning applicators, are therefore indicated. The findings also further highlight the need for checking the water level periodically in long-term dosimetry procedures.

Techno-Economic Comparison of Supercritical CO2, Steam, and Organic Rankine Cycles for Waste Heat Recovery Applications

Abstract Supercritical CO2 (sCO2) is taking a growing interest in both industry and academic communities as a promising technology capable of high efficiency, flexibility, and competitive capital costs. Many possible applications are studied in the energy field, from nuclear power plants to concentrating solar power and waste heat recovery (WHR). To evaluate the competitiveness of sCO2 cycles relative to other competing technologies, mainly steam and organic fluid Rankine cycles (ORC), a specific techno-economic analysis is needed to fairly compare the different technologies for each application, in order to find the most appropriate market position of the innovative sCO2 plants, compared to the existing steam and ORC solutions. In the present study, techno-economic analysis and optimization have been conducted focusing on WHR applications, for different sizes and cycle parameters operating conditions using an in-house simulation tool. The analyzed cycles were first optimized by aiming at maximizing the net electrical power and then aiming at minimizing the specific capital cost. As a result, compared to traditional plants, we obtained that in the first case, the more complex sCO2 cycle configuration shows competitive performance, while in the second case, the simpler sCO2 cycle configuration has a lower specific cost for the same electrical power produced (with a difference of approximately −130 €/kW compared to the steam cycle). In general, while traditional technologies confirmed a good tradeoff between performance and cost, supercritical CO2 cycles show attractive characteristics for applications requiring simplicity and compactness, guaranteeing in the meantime other technical advantages such as water-free operation.

Calcium as an innovative and effective catalyst for the synthesis of graphene-like materials from cellulose

Pyrolysis of lignocellulosic biomass (hard carbon) produces poorly graphitic biochar. In this study, nano-structured biochars were produced from microcrystalline cellulose using calcium as a non-conventional catalyst. Calcium is abundant, environmental-friendly and widely accessible. Graphitization of calcium-impregnated cellulose was carried out at 1800 °C, a temperature below 2000 °C where the graphitization usually occurs. XRD, Raman spectroscopy, high-resolution TEM together with the in-house numerical tool developed enable the quantification of the graphene fringes in the biochars. The non-impregnated cellulose biochar was composed of short and poorly stacked graphene fringes. The impregnation with 2 wt.% of calcium led to the conversion of the initial structure into a well-organized and less defective graphene-like one. The graphene-like structures obtained were composed of tens of stacked graphene fringes with a crystallite size up to 20 nm and an average interlayer spacing equal to 0.345 nm, close to the reference value of standard hexagonal graphite (0.3354 nm). The increase of the calcium concentration did not significantly improve the crystallite sizes of the graphene-like materials but rather drastically improved their rate. Our results propose a mechanism and provide new insights on the synthesis of graphene-like materials from bio-feedstocks using calcium where the literature is focused on transition metals such as iron and nickel among others. The decrease of the graphitization temperature below 2000 °C should lower the production cost as well as the environmental impact of the thermal graphene-like materials synthesis using biomass. This finding should stimulate further research in the field and broaden the application perspectives.

Real Time Micro Gas Turbines Performance Assessment Tool: Comprehensive Transient Behavior Prediction With Computationally Effective Techniques

Abstract Conventional centralized power generation is increasingly transforming into a more distributed structure. The periodic power production that is created by the renewable production unit generates the need for small-scale heat and power units. One of the promising technologies which can assist flexible power grid is micro gas turbines (mGTs). Such engines are competent candidates for small-scale combined heat and power (CHP). mGTs, as compensators for demand fluctuations, are required to work on transient and part-load conditions, creating new research challenges. A complete characterization of their dynamic behavior through a real-time simulation tool is necessary to establish effective control systems. Moreover, the energy transition requires the conversion of conventional mGTs to more sophisticated high-efficient cycles with the addition of extra components (saturation unit, aftercooler, etc.). Consequently, a modular and computationally fast real-time tool offers an asset in the development of future cycles based on the mGT concept. This paper presents the development of a numerical in-house tool implemented in Python programing language for the performance prediction of the mGT. The fundamental target of our work is to achieve high fidelity of the simulated dynamic responses. The key benefit of this tool is the low complexity component modules. The model is validated with experimental results from the VUB T100 test rig. The code reproduces the experimental data well during steady-state and transient operations as the key cycle parameters present a deviation from the measurements within the range of 1.5%.

A framework for the bi-level optimization of a generic transport aircraft fuselage using aeroelastic loads

The aeroelastic loads and design processes at the German Aerospace Center, Institute of Aeroelasticity in the framework of multi-disciplinary optimization are constantly evolving. New developments have been made in the in-house model generation tool ModGen, which allow us to create detailed fuselage models for preliminary design. As a part of the subsequent developments to integrate the fuselage structure in our aeroelastic design process, a new framework for optimizing the fuselage structure has been developed. The process is based on a bi-level optimization approach which follows a global–local optimization methodology to simplify a large optimization problem. A sub-structuring procedure is used to define stiffened panels as independent structures for local optimization. The panels are sized with stress and buckling constraints with consideration of several aeroelastic load cases. Furthermore, in this paper, we present a physical sub-structure grouping process which enables reduced number of panel optimizations and saves considerable computational effort with little compromise in the solution accuracy.