Seismic assessment of rc structures with infill masonry panels in Nepal: sensitivity analysis

Reinforced concrete (RC) buildings in Nepal are constructed as RC frames with masonry infill panels. These structures exhibit a highly non-linear inelastic behaviour resulting from the interaction between the masonry infill panels and the surrounding frames. In this context, the paper presents an extensive case study of existing RC-framed buildings in a high seismic risk area in Nepal. A sensitivity analysis of the structures with masonry infill is performed. For this, the influence of different material properties is studied, namely diagonal compressive stress, modulus of elasticity and tensile stress of masonry infill panels. Result shows the influence on the structural behaviour particularly by variation of the diagonal compressive strength of infill masonry panels

Seismic response of current RC buildings in Kathmandu Valley

RC buildings constitute the prevailing type of construction in earthquake-prone region like Kathmandu Valley. Most of these building constructions were based on conventional methods. In this context, the present paper studied the seismic behaviour of existing RC buildings in Kathmandu Valley. For this, four representative building structures with different design and construction, namely a building: (a) representing the non-engineered construction (RC1 and RC2) and (b) engineered construction (RC3 and RC4) has been selected for analysis. The dynamic properties of the case study building models are analyzed and the corresponding interaction with seismic action is studied by means of non-linear analyses. The structural response measures such as capacity curve, inter-storey drift and the effect of geometric non-linearities are evaluated for the two orthogonal directions. The effect of plan and vertical irregularity on the performance of the structures was studied by comparing the results of two engineered buildings. This was achieved through non-linear dynamic analysis with a synthetic earthquake subjected to X, Y and loading directions. The nature of the capacity curve represents the strong impact of the P-delta effect, leading to a reduction of the global lateral stiffness and reducing the strength of the structure. The non-engineered structures experience inter-storey drift demands higher than the engineered building models. Moreover, these buildings have very low lateral resistant, lesser the stiffness and limited ductility. Finally, a seismic safety assessment is performed based on the proposed drift limits. Result indicates that most of the existing buildings in Nepal exhibit inadequate seismic performance

Seismic assessment of three-storey residential buildings in Nepal

This paper evaluates the seismic performance of existing three-storey residential reinforced concrete (RC) buildings in Nepal. For this, it was designed a representative RC building structure (WDS) and the results were compared with similar buildings detailed with: i) Current Construction Practices (CCP); ii) Nepal Building Code (NBC) and iii) Modified Nepal Building Code (NBC+) recommendations. The results were analyzed and compared in terms of capacity curve, inter-storey drift and detailing of structures. The overall comparison indicates that CCP structure has a low amount of reinforcement both in beam and column sections when compared with the WDS structure. For the structure designed according with the NBC and NBC+ recommendations, improvements are clear relatively to the CCP structure, but it may be not sufficient for the demands in regions with high seismic hazard. Non-linear analysis shows that CCP and NBC structures experiences lower base shear capacity with higher inter-storey drift demand than other structures. Finally, the influence of seismic zone factor on reinforcement demand of the structure is analysed by designing the same WDS structure for a low, medium and high seismic hazard zone

Assessment of seismic strengthening solutions for existing low-rise RC buildings in Nepal

The main objective of this study is to analytically investigate the effectiveness of different strengthening solutions in upgrading the seismic performance of existing reinforced concrete (RC) buildings in Nepal. For this, four building models with different structural configurations and detailing were considered. Three possible rehabilitation solutions were studied, namely: (a) RC shear wall, (b) steel bracing, and (c) RC jacketing for all of the studied buildings. A numerical analysis was conducted with adaptive pushover and dynamic time history analysis. Seismic performance enhancement of the studied buildings was evaluated in terms of demand capacity ratio of the RC elements, capacity curve, inter-storey drift, energy dissipation capacity and moment curvature demand of the structures. Finally, the seismic safety assessment was performed based on standard drift limits, showing that retrofitting solutions significantly improved the seismic performance of existing buildings in Nepal

Earthquake loss estimation for the Kathmandu Valley

The capital city, Kathmandu, is the most developed and populated place in Nepal. The majority of the administrative offices, headquarters, numerous historical monuments, and eight World Heritages sites are in the Kathmandu Valley. However, this region is geologically located on lacustrine sediment basin, characterized by a long history of destructive earthquakes. The past events resulted in great damage of structures, losses of human life’s and property, and interrupted the social development. Therefore, earthquake disaster management is one of the most serious issues in highly seismically active regions such as the Kathmandu Valley. In recent years, the earthquake risk in this area has significantly increased due to uncontrolled development, poor construction practices with no earthquake safety consideration, and lack of awareness amongst the general public and government authorities. In this context, this study explores the realistic situation of earthquake losses due to future earthquakes in Kathmandu Valley. To this end, three municipalities: (a) Kathmandu metropolitan city (KMC), (b) Lalitpur Sub-Metropolitan City (LSMC) and (c) Bhaktapur Municipality (BMC) are selected for study. The earthquake loss estimation in the selected municipalities is performed through the combination of seismic hazard, structural vulnerability, and exposure data. For what concerns the seismic input, various earthquake scenarios considering four seismic sources in Nepal were adopted. Regarding the exposure, data about the type of existing buildings, population, and ward level distribution of building typologies is estimated from the recent national census survey of 2011. The economic losses due to the scenario earthquakes are determined using fragility functions. The commonly used standard fragility curves are adopted for adobe, brick/stone with mud mortar buildings, and brick/stone with cement mortar buildings. For the reinforced concrete structures, a new fragility model was derived considering four construction typologies: i) current construction practices (CCP), ii) structures according to the Nepal buildings code (NBC), iii) structures according to the modified Nepal building code (NBC+) and iv) well designed structures (WDS). In this study, a set of fragility functions is converted into a vulnerability model through a consequences model. Finally, the ward level distribution of damage for each building typology, building losses and the corresponding economic loss for each scenario earthquake is obtained using the OpenQuake-engine. The distribution of damage within the Kathmandu Valley is currently being employing in the development of a shelter model for the region, involving various local authorities and decision makers

Developing Cybersecurity Awareness: A case study on Enhancing Employee Training in a Marine Manufacturing SME

The objective of this thesis project was to develop and implement a cybersecurity awareness training programme tailored to employees at Oceanvolt, a marine manufacturing SME. Commissioned by Oceanvolt, the project aimed to identify existing knowledge gaps and develop a comprehensive training solution designed to enhance cybersecurity awareness in employees. The development task involved designing a practical, evidence-based training session obtained from the internal survey. The theoretical framework was based on NIST Cybersecurity Framework (CSF) 2.0 and the ADDIE instructional design model, which provided structured guidance for analysing needs, designing content and evaluating impact. The research utilized mixed-methods approach, first by baselining cybersecurity awareness through the survey and then, through the design and delivery of a one-session live training including interactive demonstrations. A post training survey and qualitative feedback were then used to evaluate effectiveness. Key findings showed that employees demonstrated strong individual cybersecurity behaviours in some respects. However, awareness of governance roles, recovery procedure, and formal security policy were limited. The training session significantly improved confidence and perceived relevance, as shown by the post training survey. Open feedback revealed strong employee engagement, calls for more company-specific context and support for monthly refreshers. The executive leadership requested the development of formal cybersecurity policy immediately following the session. The thesis concludes that even a short, practical targeted training initiative supported by leadership and based on real-world context can enhance cybersecurity culture and procedural change within an SME

Inhibition of bacterial and human zinc-metalloproteases

Antibiotic resistance is one of the major challenges in the present era and it is drastically increasing with the increase in time because of the overuse and misuse of antibiotics. Therefore, there is a demand of new antibiotics with new modes of action or other innovative strategies to overcome bacterial infections as soon as possible. The zinc metalloproteases Themolysin (TLN), Pseudolysin (PLN) and Aureolysin (ALN) are important bacterial virulence factors and the inhibition of these bacterial virulence factors is believed to be a new treatment option of bacterial infections. However, in order to have a therapeutic value, inhibitors of these enzymes should not interfere strongly with the activity of human zinc metalloproteases. In the present thesis, 26 compounds were tested for the inhibition of TLN, PLN, ALN and the human matrix metalloproteases-14(MMP-14). The compounds were selected from a previous virtual screening project at the research group. The inhibition of the compounds was tested by measuring the enzyme activity of PLN, TLN ALN and MMP-14 after exposure of the test compounds. The time resolved fluorescence by the use of fluorogenic substrates was used to measure the enzyme activity. The results showed that some of the compounds inhibited the enzyme activity by 30%-40% and they were not considered as slow binders as there was no significant change in activity with respect to the time. Compounds with highest rate of inhibition in enzyme assays were selected and proceed for molecular modeling studies by docking and MMGBSA calculations. The best compounds were compared with a known strong inhibitor of the zinc- metalloproteases in the molecular modeling part

EVALUATION OF THE INDOOR ENVIRONMENT AND PERCEIVED IEQ IN NORWEGIAN SCHOOLS WITH MACHINE LEARNING MODELS

Innemiljøkvalitet (IEQ) er et viktig aspekt ved klasserommene som bestemmer situasjonen for komfort, helse og produktivitet. Målt og oppfattet IEQ er to vanligste metoder foreslått av internasjonal standard og mange vitenskapelige studier for å evaluere IEQ. Det er imidlertid nødvendig å finne ut den viktigste som er oppfylt av denne studien. Maskinlæringsmodellen (ML) ble brukt til å forutsi elevenes oppfatning av temperatur, luftkvalitet, helsestatus gjennom målte miljøparametere og finne ut eksisterende forhold mellom målte miljøparametere og studentenes oppfatning. Til slutt ble nøyaktigheten av ML predikert oppfatning og tradisjonell statistisk modell (TSM) predikert oppfatning sammenlignet. Data ble samlet inn i syv dager fra to klasser hver fra tre norske skoler: Bratteberg, Øyra og Brannfjell. Predikert gjennomsnittlig stemme (PMV), predikert prosentandel misfornøyd (PPD), prosentandel misfornøyd (PD) som funksjon av CO2, PMV som funksjon av CO2 og VOC og relativ ytelse sammen med registrerte innemiljøparametere; lufttemperatur, relativ luftfuktighet, CO2 og VOC målt av frittstående instrumenter (AirTHINGS)™ installert i utvalgte klasserom ga til sammen den målte IEQ. Studentenes oppfatning av luftkvalitet, helsestatus og temperatur ble samlet inn ved hjelp av spørreundersøkelse som ga faktisk IEQ. Gjennomsnittlig svarprosent var 62,0 0 % (standardavvik SD=26,00). PD som funksjon av akseptabilitet (ACC) skala og PPD som funksjon av termisk sensasjonsstemme (TSV) ga oppfattet IEQ. Lufttemperatur, CO2 og PPD i henhold til EN 16798:1, 2019 var av høyere kategori ved to av tre skoler og presterte bedre enn anbefalt minimumskrav. Ser vi alle skolene under ett, var relativ luftfuktighet under nedre grense på 20 % i det meste av perioden ved to av tre skoler, og mer enn 17,00 % av registrerte VOC-verdier var over øvre grense på 500 ppb. Sammenligning av PMV som funksjon av CO2 og VOC med Fangers ACC-skala for innendørs luftkvalitet (IAQ) indikerte IAQ på mellom klart akseptabelt og akseptabelt område, mens beregnet gjennomsnittlig relativ ytelse i klasserommene var 96,00%. På maksimum viste det faktiske IEQ-resultatet at 20,00% velgere var misfornøyde med luftkvalitet og temperatur og 19,00% velgere hadde dårlig helsestatus. Oppfattet IEQ viste, det var 38,00% (SD = 9,70) PD oppnådd som en funksjon av ACC-skala og 10,00% (SD = 8,70) PPD som en funksjon av TSV som ikke kunne kategoriseres i henhold til EN 16798: 1,2019 som indikerer muligheten for helseproblemer blant studenter på grunn av både luftkvalitet og termisk miljø. Målt metode for evaluering av IEQ bidro til å sikre om innemiljøparametere er innenfor anbefalt grense, mens oppfattet metode for evaluering av IEQ bidro til å sikre om det er helseproblemer blant studenter. Derfor viste begge metodene seg å være like viktige mens de evaluerte IEQ. Regresjonsmodellen Extra tree (ET) og random forest (RF) ble valgt for å forutsi oppfatningen av elevenes IEQ gjennom målte miljøparametere, inkludert utetemperatur, relativ fuktighet og vindhastighet sammen med målte innemiljøparametere. Med en gjennomsnittlig nøyaktighet på 0,82 (SD = 0,05) ble ML-modellen bevist effektiv mens den predikerte oppfatningen av elevene. Miljøparametere innendørs VOC, innendørs CO2, innetemperatur og utendørs vindhastighet var viktige for å forutsi elevenes oppfatning av luftkvalitet og helsestatus på alle skoler. Dette viste at forholdet mellom oppfatning om helse, luftkvalitet og viktige miljøparametere er signifikant. Selv om nøyaktigheten var høy mens man forutsa oppfatning mot temperatur, var rangeringen av funksjonsvariabler i henhold til deres betydning vanskelig å tolke. Oppfatning om luft, temperatur og helse var viktig mens man predikerte teoretisk beregnet relativ ytelse. Ved hjelp av lineær regresjon viste sammenligning av nøyaktighet av ML-predikert oppfatning og TSM-predikert oppfatning en klar fordel med ML-modellen fremfor TSM med tanke på datakvalitet, funksjonsvariabler og miljø som skole. (Note: This abstract was translated using microsoft word language translation feature.)Indoor environment quality (IEQ) is an important aspect of the classrooms that determines the situation of comfort, health and productivity. Measured and perceived IEQ are two most common methods suggested by international standard and many scholarly studies to evaluate IEQ. However, it is required to find out the most important one which is fulfilled by this study. Machine learning (ML) model was applied to predict the perception of students’ regarding temperature, air quality, their health status through measured environment parameters and find out existing relationships between measured environment parameters and students’ perception. Lastly, Accuracy of ML predicted perception and traditional statistical model (TSM) predicted perception were compared. Data were collected for seven days from two classes each from three Norwegian schools: Bratteberg, Øyra and Brannfjell. Predicted mean vote (PMV), predicted percentage dissatisfied (PPD), percentage dissatisfied (PD) as function of CO2, PMV as function of CO2 & VOC and relative performance along with recorded indoor environment parameters; air temperature, relative humidity, CO2 and VOC measured by stand-alone instruments (AirTHINGS™) installed in selected classrooms altogether provided the measured IEQ. Students’ perception regarding air quality, health status and temperature were collected using survey which provided actual IEQ. Average response rate was 62.00% (standard deviation SD=26.00). PD as function of acceptability (ACC) scale and PPD as function of thermal sensation vote (TSV) provided perceived IEQ. Air temperature, CO2 and PPD according to EN 16798:1, 2019 were of higher category at two out of three schools and performed better than the recommended minimum requirement. Looking all school together, relative humidity was below the lower limit of 20 % for most of the period at two out of three schools and more than 17.00% of registered VOC values were above the upper limit of 500 ppb. Comparing PMV as function of CO2 & VOC with Fanger’s ACC scale for indoor air quality (IAQ) indicated IAQ of between clearly accept able and acceptable range whereas calculated average relative performance in the classrooms was 96.00%. At maximum, actual IEQ result showed 20.00% voters were dissatisfied with air quality and temperature and 19.00% voters had poor health status. Perceived IEQ showed, there were 38.00% (SD = 9.70) PD obtained as a function of ACC scale and 10.00% (SD = 8.70) PPD as a function of TSV which could not be categorized according to EN 16798:1,2019 indicating the possibility of health problems among students’ due to both air quality and thermal environment. Measured method of evaluating IEQ helped ensuring whether indoor environment parameters are within recommended limit whereas perceived method of evaluating IEQ helped ensuring whether there are any health issues among students. Hence, both methods found out to be equally important while evaluating IEQ. Extra tree (ET) and random forest (RF) regression model were chosen to predict perception of students’ regarding IEQ through measured environment parameters including outdoor temperature, relative humidity and wind speed along with measured indoor environment parameters. With an average accuracy of 0.82 (SD = 0.05), the ML model was proven effective while predicting perception of students. Environment parameters indoor VOC, indoor CO2, indoor temperature and outdoor wind speed were important for predicting students’ perception towards air quality and health status in all schools. This proved that the relationship between perception regarding health, air quality and important environment parameters is significant. Even though the accuracy was high while predicting perception towards temperature, the rank of feature variables as per their importance was difficult to interpret. Perception regarding air, temperature and health were important while predicting theoretically calculated relative performance. Using linear regression, comparison of accuracy of ML predicted perception and TSM predicted perception showed distinct advantage of ML model over TSM considering data quality, feature variables and environment as school

An Analysis on the Correlation Between Atmospheric Parameters and TOA Reflectance of Pseudo Invariant Calibration Sites (PICS)

The objective of this work is to understand and quantify the relationship(s) between atmospheric parameters and TOA reflectance. The analysis uses Landsat-7 ETM+ and Landsat-8 OLI images data acquired over the Algodones Dunes and a desert site near Wadi ad-Dawasir, Saudi Arabia. The analysis focuses on atmospheric water content and barometric pressure, as ground truth measurements of these quantities are likely to be readily available from relatively nearby weather stations. Section II of the paper discusses the methodology used in the analysis. Section III presents the analysis results. Finally, Section IV provides a summary and considers potential directions for future investigation

Counter-propagating radiative shock experiments on the Orion laser and the formation of radiative precursors

We present results from new experiments to study the dynamics of radiative shocks, reverse shocks and radiative precursors. Laser ablation of a solid piston by the Orion high-power laser at AWE Aldermaston UK was used to drive radiative shocks into a gas cell initially pressurised between $0.1$ and $1.0 \ bar with different noble gases. Shocks propagated at {80 \pm 10 \ km/s} and experienced strong radiative cooling resulting in post-shock compressions of { \times 25 \pm 2}. A combination of X-ray backlighting, optical self-emission streak imaging and interferometry (multi-frame and streak imaging) were used to simultaneously study both the shock front and the radiative precursor. These experiments present a new configuration to produce counter-propagating radiative shocks, allowing for the study of reverse shocks and providing a unique platform for numerical validation. In addition, the radiative shocks were able to expand freely into a large gas volume without being confined by the walls of the gas cell. This allows for 3-D effects of the shocks to be studied which, in principle, could lead to a more direct comparison to astrophysical phenomena. By maintaining a constant mass density between different gas fills the shocks evolved with similar hydrodynamics but the radiative precursor was found to extend significantly further in higher atomic number gases (\sim$$4$ times further in xenon than neon). Finally, 1-D and 2-D radiative-hydrodynamic simulations are presented showing good agreement with the experimental data.Comment: HEDLA 2016 conference proceeding